diff --git a/NAMESPACE b/NAMESPACE index 4efc223c..0beed367 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -1,11 +1,10 @@ # Generated by roxygen2: do not edit by hand -export(BooleDS) export(absDS) export(asCharacterDS) export(asDataMatrixDS) -export(asFactorDS1) -export(asFactorDS2) +export(asFactor1DS) +export(asFactor2DS) export(asFactorSimpleDS) export(asIntegerDS) export(asListDS) @@ -13,6 +12,7 @@ export(asLogicalDS) export(asMatrixDS) export(asNumericDS) export(aucDS) +export(booleDS) export(boxPlotGGDS) export(boxPlotGG_data_TreatmentDS) export(boxPlotGG_data_Treatment_numericDS) @@ -30,8 +30,8 @@ export(corTestDS) export(covDS) export(dataFrameDS) export(dataFrameSortDS) -export(dataFrameSubsetDS1) -export(dataFrameSubsetDS2) +export(dataFrameSubset1DS) +export(dataFrameSubset2DS) export(densityGridDS) export(dimDS) export(dmtC2SDS) @@ -44,41 +44,41 @@ export(gamlssDS) export(getAllLevelsDS) export(getClassAllColsDS) export(getWGSRDS) -export(glmDS1) -export(glmDS2) +export(glm1DS) +export(glm2DS) export(glmPredictDS.ag) export(glmPredictDS.as) +export(glmSLMA1DS) +export(glmSLMA2DS) export(glmSLMADS.assign) -export(glmSLMADS1) -export(glmSLMADS2) export(glmSummaryDS.ag) export(glmSummaryDS.as) +export(glmerSLMA2DS) export(glmerSLMADS.assign) -export(glmerSLMADS2) export(heatmapPlotDS) export(hetcorDS) -export(histogramDS1) -export(histogramDS2) +export(histogram1DS) +export(histogram2DS) export(igb_standardsDS) export(isNaDS) export(isValidDS) -export(kurtosisDS1) -export(kurtosisDS2) +export(kurtosis1DS) +export(kurtosis2DS) export(lengthDS) export(levelsDS) -export(lexisDS1) -export(lexisDS2) -export(lexisDS3) +export(lexis1DS) +export(lexis2DS) +export(lexis3DS) export(listDS) export(listDisclosureSettingsDS) +export(lmerSLMA2DS) export(lmerSLMADS.assign) -export(lmerSLMADS2) export(logDS) export(lsDS) export(lsplineDS) export(matrixDS) -export(matrixDetDS1) -export(matrixDetDS2) +export(matrixDet1DS) +export(matrixDet2DS) export(matrixDiagDS) export(matrixDimnamesDS) export(matrixInvertDS) @@ -111,13 +111,13 @@ export(sampleDS) export(scatterPlotDS) export(seqDS) export(setSeedDS) -export(skewnessDS1) -export(skewnessDS2) +export(skewness1DS) +export(skewness2DS) export(sqrtDS) export(table1DDS) +export(table2DS) export(tableDS) export(tableDS.assign) -export(tableDS2) export(tapplyDS) export(tapplyDS.assign) export(unListDS) diff --git a/R/asFactorDS1.R b/R/asFactor1DS.R similarity index 97% rename from R/asFactorDS1.R rename to R/asFactor1DS.R index c6c0445a..ad1714b2 100644 --- a/R/asFactorDS1.R +++ b/R/asFactor1DS.R @@ -10,7 +10,7 @@ #' @author Tim Cadman, Genomics Coordination Centre, UMCG, Netherlands #' @export #' -asFactorDS1 <- function(input.var.name=NULL){ +asFactor1DS <- function(input.var.name=NULL){ ################################################################## #MODULE 1: CAPTURE THE nfilter SETTINGS # thr<-dsBase::listDisclosureSettingsDS() # @@ -49,5 +49,5 @@ asFactorDS1 <- function(input.var.name=NULL){ } #AGGREGATE FUNCTION -# asFactorDS1 +# asFactor1DS diff --git a/R/asFactorDS2.R b/R/asFactor2DS.R similarity index 96% rename from R/asFactorDS2.R rename to R/asFactor2DS.R index af45a47f..838d5108 100644 --- a/R/asFactorDS2.R +++ b/R/asFactor2DS.R @@ -18,7 +18,7 @@ #' @author Tim Cadman, Genomics Coordination Centre, UMCG, Netherlands #' @export #' -asFactorDS2 <- function(input.var.name=NULL, all.unique.levels.transmit=NULL, fixed.dummy.vars=NULL, baseline.level=NULL){ +asFactor2DS <- function(input.var.name=NULL, all.unique.levels.transmit=NULL, fixed.dummy.vars=NULL, baseline.level=NULL){ input.var <- .loadServersideObject(input.var.name) @@ -48,4 +48,4 @@ asFactorDS2 <- function(input.var.name=NULL, all.unique.levels.transmit=NULL, fi } #ASSIGN FUNCTION -# asFactorDS2 \ No newline at end of file +# asFactor2DS diff --git a/R/BooleDS.R b/R/booleDS.R similarity index 98% rename from R/BooleDS.R rename to R/booleDS.R index ee967f7f..04e26e7f 100644 --- a/R/BooleDS.R +++ b/R/booleDS.R @@ -1,5 +1,5 @@ #' -#' @title BooleDS +#' @title booleDS #' @description Converts the individual elements of a vector or other object into #' Boolean indicators. #' @details The function converts the input vector into Boolean indicators. @@ -26,7 +26,7 @@ #' @return the levels of the input variable. #' @export #' -BooleDS <- function(V1.name=NULL, V2.name=NULL, Boolean.operator.n=NULL, na.assign.text, numeric.output=TRUE){ +booleDS <- function(V1.name=NULL, V2.name=NULL, Boolean.operator.n=NULL, na.assign.text, numeric.output=TRUE){ # Check Permissive Privacy Control Level. dsBase::checkPermissivePrivacyControlLevel(c('permissive', 'banana', 'carrot')) diff --git a/R/dataFrameSubsetDS1.R b/R/dataFrameSubset1DS.R similarity index 95% rename from R/dataFrameSubsetDS1.R rename to R/dataFrameSubset1DS.R index 5f5e0c52..011a2cc2 100644 --- a/R/dataFrameSubsetDS1.R +++ b/R/dataFrameSubset1DS.R @@ -1,46 +1,46 @@ #' -#' @title dataFrameSubsetDS1 an aggregate function called by ds.dataFrameSubset +#' @title dataFrameSubset1DS an aggregate function called by ds.dataFrameSubset #' @description First serverside function for subsetting a data frame by row or by column. #' @details A data frame is a list of variables all with the same number of rows, #' which is of class 'data.frame'. For all details see the help header for ds.dataFrameSubset #' @param df.name a character string providing the name for the data.frame #' to be sorted. argument generated and passed directly to -#' dataFrameSubsetDS1 by ds.dataFrameSubset +#' dataFrameSubset1DS by ds.dataFrameSubset #' @param V1.name A character string specifying the name of a subsetting vector #' to which a Boolean operator will be applied to define the subset to be created. #' argument generated and passed directly to -#' dataFrameSubsetDS1 by ds.dataFrameSubset +#' dataFrameSubset1DS by ds.dataFrameSubset #' @param V2.name A character string specifying the name of the vector #' or scalar to which the values in the vector specified by the argument #' is to be compared. #' argument generated and passed directly to -#' dataFrameSubsetDS1 by ds.dataFrameSubset +#' dataFrameSubset1DS by ds.dataFrameSubset #' @param Boolean.operator.n A character string specifying one of six possible Boolean operators: #' '==', '!=', '>', '>=', '<', '<=' #' argument generated and passed directly to -#' dataFrameSubsetDS1 by ds.dataFrameSubset +#' dataFrameSubset1DS by ds.dataFrameSubset #' @param keep.cols a numeric vector specifying the numbers of the columns to be kept in the #' final subset when subsetting by column. For example: keep.cols=c(2:5,7,12) will keep #' columns 2,3,4,5,7 and 12. #' argument generated and passed directly to -#' dataFrameSubsetDS1 by ds.dataFrameSubset +#' dataFrameSubset1DS by ds.dataFrameSubset #' @param rm.cols a numeric vector specifying the numbers of the columns to be removed before #' creating the final subset when subsetting by column. For example: rm.cols=c(2:5,7,12) #' will remove columns 2,3,4,5,7 and 12. #' argument generated and passed directly to -#' dataFrameSubsetDS1 by ds.dataFrameSubset +#' dataFrameSubset1DS by ds.dataFrameSubset #' @param keep.NAs logical, if TRUE any NAs in the vector holding the final Boolean vector #' indicating whether a given row should be included in the subset will be converted into #' 1s and so they will be included in the subset. Such NAs could be caused by NAs in #' either or . If FALSE or NULL NAs in the final Boolean vector will #' be converted to 0s and the corresponding row will therefore be excluded from the subset. #' argument generated and passed directly to -#' dataFrameSubsetDS1 by ds.dataFrameSubset +#' dataFrameSubset1DS by ds.dataFrameSubset #' @return This first serverside function called by ds.dataFrameSubset provides #' first level traps for a comprehensive series of disclosure risks which can be -#' returned directly to the clientside because dataFrameSubsetDS1 is an aggregate +#' returned directly to the clientside because dataFrameSubset1DS is an aggregate #' function. The second serverside function called by ds.dataFrameSubset -#' (dataFrameSubsetDS2) carries out most of the same disclosure tests, but it is +#' (dataFrameSubset2DS) carries out most of the same disclosure tests, but it is #' an assign function because it writes the subsetted data.frame to the serverside. #' In consequence, it records error messages as studysideMessages which can only be #' retrieved using ds.message @@ -48,7 +48,7 @@ #' @author Tim Cadman, Genomics Coordination Centre, UMCG, Netherlands #' @export #' -dataFrameSubsetDS1 <- function(df.name=NULL,V1.name=NULL,V2.name=NULL,Boolean.operator.n=NULL,keep.cols=NULL,rm.cols=NULL,keep.NAs=NULL){ +dataFrameSubset1DS <- function(df.name=NULL,V1.name=NULL,V2.name=NULL,Boolean.operator.n=NULL,keep.cols=NULL,rm.cols=NULL,keep.NAs=NULL){ # Check Permissive Privacy Control Level. dsBase::checkPermissivePrivacyControlLevel(c('permissive', 'banana', 'carrot')) @@ -303,4 +303,4 @@ if(sum(is.na(keep.code.n))>0){ } # AGGREGATE FUNCTION -# dataFrameSubsetDS1 +# dataFrameSubset1DS diff --git a/R/dataFrameSubsetDS2.R b/R/dataFrameSubset2DS.R similarity index 94% rename from R/dataFrameSubsetDS2.R rename to R/dataFrameSubset2DS.R index ff1f2bee..84008883 100644 --- a/R/dataFrameSubsetDS2.R +++ b/R/dataFrameSubset2DS.R @@ -1,42 +1,41 @@ -###############################################################################|###################| 80 and 100 - -#' @title dataFrameSubsetDS2 an assign function called by ds.dataFrameSubset +#' +#' @title dataFrameSubset2DS an assign function called by ds.dataFrameSubset #' @description Second serverside function for subsetting a data frame by row or by column. #' @details A data frame is a list of variables all with the same number of rows, #' which is of class 'data.frame'. For all details see the help header for ds.dataFrameSubset #' @param df.name a character string providing the name for the data.frame #' to be sorted. argument generated and passed directly to -#' dataFrameSubsetDS2 by ds.dataFrameSubset +#' dataFrameSubset2DS by ds.dataFrameSubset #' @param V1.name A character string specifying the name of a subsetting vector #' to which a Boolean operator will be applied to define the subset to be created. #' argument generated and passed directly to -#' dataFrameSubsetDS2 by ds.dataFrameSubset +#' dataFrameSubset2DS by ds.dataFrameSubset #' @param V2.name A character string specifying the name of the vector #' or scalar to which the values in the vector specified by the argument #' is to be compared. #' argument generated and passed directly to -#' dataFrameSubsetDS2 by ds.dataFrameSubset +#' dataFrameSubset2DS by ds.dataFrameSubset #' @param Boolean.operator.n A character string specifying one of six possible Boolean operators: #' '==', '!=', '>', '>=', '<', '<=' #' argument generated and passed directly to -#' dataFrameSubsetDS2 by ds.dataFrameSubset +#' dataFrameSubset2DS by ds.dataFrameSubset #' @param keep.cols a numeric vector specifying the numbers of the columns to be kept in the #' final subset when subsetting by column. For example: keep.cols=c(2:5,7,12) will keep #' columns 2,3,4,5,7 and 12. #' argument generated and passed directly to -#' dataFrameSubsetDS2 by ds.dataFrameSubset +#' dataFrameSubset2DS by ds.dataFrameSubset #' @param rm.cols a numeric vector specifying the numbers of the columns to be removed before #' creating the final subset when subsetting by column. For example: rm.cols=c(2:5,7,12) #' will remove columns 2,3,4,5,7 and 12. #' argument generated and passed directly to -#' dataFrameSubsetDS2 by ds.dataFrameSubset +#' dataFrameSubset2DS by ds.dataFrameSubset #' @param keep.NAs logical, if TRUE any NAs in the vector holding the final Boolean vector #' indicating whether a given row should be included in the subset will be converted into #' 1s and so they will be included in the subset. Such NAs could be caused by NAs in #' either or . If FALSE or NULL NAs in the final Boolean vector will #' be converted to 0s and the corresponding row will therefore be excluded from the subset. #' argument generated and passed directly to -#' dataFrameSubsetDS2 by ds.dataFrameSubset +#' dataFrameSubset2DS by ds.dataFrameSubset #' @return the object specified by the argument (or default name '_subset') #' initially specified in calling ds.dataFrameSubset. The output object (the required #' subsetted data.frame called is written to the serverside. In addition, @@ -44,7 +43,7 @@ #' indicating whether has been created in each data source and if so whether #' it is in a valid form. If its form is not valid in at least one study - e.g. because #' a disclosure trap was tripped and creation of the full output object was blocked - -#' dataFrameSubsetDS2 (via ds.dataFrame()) also returns any studysideMessages +#' dataFrameSubset2DS (via ds.dataFrame()) also returns any studysideMessages #' that can explain the error in creating #' the full output object. As well as appearing on the screen at run time,if you wish to #' see the relevant studysideMessages at a later date you can use the \code{ds.message} @@ -57,7 +56,7 @@ #' @author Tim Cadman, Genomics Coordination Centre, UMCG, Netherlands #' @export #' -dataFrameSubsetDS2<-function(df.name=NULL,V1.name=NULL, V2.name=NULL, Boolean.operator.n=NULL,keep.cols=NULL, rm.cols=NULL, keep.NAs=NULL){ +dataFrameSubset2DS<-function(df.name=NULL,V1.name=NULL, V2.name=NULL, Boolean.operator.n=NULL,keep.cols=NULL, rm.cols=NULL, keep.NAs=NULL){ # Check Permissive Privacy Control Level. dsBase::checkPermissivePrivacyControlLevel(c('permissive', 'banana', 'carrot')) @@ -327,4 +326,4 @@ return(df.subset) } #ASSIGN FUNCTION -# dataFrameSubsetDS2 +# dataFrameSubset2DS diff --git a/R/glmDS1.R b/R/glm1DS.R similarity index 97% rename from R/glmDS1.R rename to R/glm1DS.R index 3fc2ab3c..38760036 100644 --- a/R/glmDS1.R +++ b/R/glm1DS.R @@ -1,9 +1,9 @@ #' -#' @title glmDS1 called by ds.glm +#' @title glm1DS called by ds.glm #' @description This is the first server-side aggregate function called by ds.glm #' @details It is an #' aggregation function that sets up the model structure -#' and creates the starting beta.vector that feeds, via ds.glm, into glmDS2 to enable +#' and creates the starting beta.vector that feeds, via ds.glm, into glm2DS to enable #' iterative fitting of the generalized linear model that has been #' been specified. For more details please see the extensive header for ds.glm. #' @param formula a glm() formula consistent with R syntax eg U~x+y+Z to regress @@ -22,7 +22,7 @@ #' @author Tim Cadman, Genomics Coordination Centre, UMCG, Netherlands #' @export #' -glmDS1 <- function(formula, family, weights, offset, data){ +glm1DS <- function(formula, family, weights, offset, data){ ############################################################# @@ -202,11 +202,11 @@ if(!is.null(offsetvar)) } } - #If y, X or w data are invalid, or the model is overparameterized, this will be detected by glmDS1 + #If y, X or w data are invalid, or the model is overparameterized, this will be detected by glm1DS #and passed to ds.glm resulting in a warning and a controlled shut down of the function. #But in case someone modifies the client side function to circumvent the trap, so the - #error is only apparent once the main main iterations have started via glmDS2 - #the equivalent tests in glmDS2 will destroy the info.matrix and score.vector in the affected study so + #error is only apparent once the main main iterations have started via glm2DS + #the equivalent tests in glm2DS will destroy the info.matrix and score.vector in the affected study so #the model fitting will simply terminate. if(!(y.invalid>0||w.invalid>0||o.invalid>0||sum(Xpar.invalid)>0||glm.saturation.invalid>0)){ @@ -221,6 +221,6 @@ if(!is.null(offsetvar)) } #AGGREGATE FUNCTION -# glmDS1 +# glm1DS diff --git a/R/glmDS2.R b/R/glm2DS.R similarity index 98% rename from R/glmDS2.R rename to R/glm2DS.R index caff48f0..17dc1bb0 100644 --- a/R/glmDS2.R +++ b/R/glm2DS.R @@ -1,9 +1,9 @@ #' -#' @title glmDS2 called by ds.glm +#' @title glm2DS called by ds.glm #' @description This is the second server-side aggregate function called by ds.glm. #' @details It is an aggregate function that uses the model structure and starting -#' beta.vector constructed by glmDS1 to iteratively fit the generalized linear model -#' that has been specified. The function glmDS2 also carries out a series of disclosure +#' beta.vector constructed by glm1DS to iteratively fit the generalized linear model +#' that has been specified. The function glm2DS also carries out a series of disclosure #' checks and if the arguments or data fail any of those tests, #' model construction is blocked and an appropriate serverside error message is #' created and returned to ds.glm on the clientside. @@ -25,7 +25,7 @@ #' @return List with values from GLM model #' @export #' -glmDS2 <- function (formula, family, beta.vect, offset, weights, dataName) { +glm2DS <- function (formula, family, beta.vect, offset, weights, dataName) { ############################################################# #MODULE 1: CAPTURE THE nfilter SETTINGS @@ -266,7 +266,7 @@ glmDS2 <- function (formula, family, beta.vect, offset, weights, dataName) { #score.vector and information.matrix in the study with the problem. #So this will make model fail without explanation - #Disclosure code from glmDS1 + #Disclosure code from glm1DS errorMessage.combined <- NULL @@ -335,7 +335,7 @@ glmDS2 <- function (formula, family, beta.vect, offset, weights, dataName) { #CHECK W VECTOR VALIDITY w.invalid <- 0 - #Keep same object name as in glmDS1 + #Keep same object name as in glm1DS w.vect <- weightsvar unique.values.noNA.w <- unique(w.vect[stats::complete.cases(w.vect)]) @@ -390,4 +390,4 @@ glmDS2 <- function (formula, family, beta.vect, offset, weights, dataName) { } # AGGREGATE FUNCTION -# glmDS2 +# glm2DS diff --git a/R/glmSLMADS1.R b/R/glmSLMA1DS.R similarity index 96% rename from R/glmSLMADS1.R rename to R/glmSLMA1DS.R index 5e594bf4..e54d42b3 100644 --- a/R/glmSLMADS1.R +++ b/R/glmSLMA1DS.R @@ -2,7 +2,7 @@ #' @description Fits a generalized linear model (GLM) on data from single or multiple sources #' with pooled co-analysis across studies being based on SLMA (Study Level Meta Analysis). #' @details glmSLMADS.assign is an aggregate function called by clientside function ds.glmSLMA. -#' ds.glmSLMA also calls another aggregate function glmSLMADS2 +#' ds.glmSLMA also calls another aggregate function glmSLMA2DS #' and an assign function glmSLMADS.assign #' For more detailed information see help for ds.glmSLMA. #' @param formula a glm formula, specified in call to ds.glmSLMA @@ -20,7 +20,7 @@ #' @author Tim Cadman, Genomics Coordination Centre, UMCG, Netherlands #' @export -glmSLMADS1<- function(formula, family, weights, offset, data){ +glmSLMA1DS<- function(formula, family, weights, offset, data){ errorMessage="No errors" @@ -198,11 +198,11 @@ if(!is.null(offsetvar)) } } - #If y, X, weights or offset data are invalid, or the model is overparameterized, this will be detected by glmDS1 + #If y, X, weights or offset data are invalid, or the model is overparameterized, this will be detected by glm1DS #and passed to ds.glm resulting in a warning and a controlled shut down of the function. #But in case someone modifies the client side function to circumvent the trap, so the - #error is only apparent once the main main iterations have started via glmDS2 - #the equivalent tests in glmDS2 will destroy the info.matrix and score.vector in the affected study so + #error is only apparent once the main main iterations have started via glm2DS + #the equivalent tests in glm2DS will destroy the info.matrix and score.vector in the affected study so #the model fitting will simply terminate. if(!(y.invalid>0||w.invalid>0||o.invalid>0||sum(Xpar.invalid)>0||glm.saturation.invalid>0)){ @@ -218,4 +218,4 @@ if(!is.null(offsetvar)) } #AGGREGATE FUNCTION -# glmSLMADS1 +# glmSLMA1DS diff --git a/R/glmSLMADS2.R b/R/glmSLMA2DS.R similarity index 98% rename from R/glmSLMADS2.R rename to R/glmSLMA2DS.R index 20d698ae..6ba6a478 100644 --- a/R/glmSLMADS2.R +++ b/R/glmSLMA2DS.R @@ -2,7 +2,7 @@ #' @description Fits a generalized linear model (GLM) on data from single or multiple sources #' with pooled co-analysis across studies being based on SLMA (Study Level Meta Analysis). #' @details glmSLMADS.assign is an aggregate function called by clientside function ds.glmSLMA. -#' ds.glmSLMA also calls another aggregate function glmSLMADS2 +#' ds.glmSLMA also calls another aggregate function glmSLMA2DS #' and an assign function glmSLMADS.assign #' For more detailed information see help for ds.glmSLMA. #' @param formula a glm formula, specified in call to ds.glmSLMA @@ -24,7 +24,7 @@ #' @author Paul Burton for DataSHIELD Development Team (14/7/20) #' @author Tim Cadman, Genomics Coordination Centre, UMCG, Netherlands #' @export -glmSLMADS2 <- function(formula, family, offset, weights, newobj, dataName){ +glmSLMA2DS <- function(formula, family, offset, weights, newobj, dataName){ ############################################################# #MODULE 1: CAPTURE THE nfilter SETTINGS # @@ -286,4 +286,4 @@ if(disclosure.risk==0) } # AGGREGATE FUNCTION -# glmSLMADS2 +# glmSLMA2DS diff --git a/R/glmSLMADS.assign.R b/R/glmSLMADS.assign.R index 3448aed3..4e21edaf 100644 --- a/R/glmSLMADS.assign.R +++ b/R/glmSLMADS.assign.R @@ -2,7 +2,7 @@ #' @description Fits a generalized linear model (GLM) on data from single or multiple sources #' with pooled co-analysis across studies being based on SLMA (Study Level Meta Analysis). #' @details glmSLMADS.assign is an assign function called by clientside function ds.glmSLMA. -#' ds.glmSLMA also calls two aggregate functions glmSLMADS1 and glmSLMADS2. +#' ds.glmSLMA also calls two aggregate functions glmSLMA1DS and glmSLMA2DS. #' For more detailed information see help for ds.glmSLMA. #' @param formula a glm formula, specified in call to ds.glmSLMA #' @param family a glm family, specified in call to ds.glmSLMA diff --git a/R/glmerSLMADS2.R b/R/glmerSLMA2DS.R similarity index 98% rename from R/glmerSLMADS2.R rename to R/glmerSLMA2DS.R index 480db660..c00875b8 100644 --- a/R/glmerSLMADS2.R +++ b/R/glmerSLMA2DS.R @@ -1,8 +1,8 @@ #' @title Fitting generalized linear mixed effect models - serverside function -#' @description glmerSLMADS2 fits a generalized linear mixed effects model +#' @description glmerSLMA2DS fits a generalized linear mixed effects model #' (glme) - e.g. a logistic or Poisson regression model including both fixed and random effects #' - on data from one or multiple sources with pooling via SLMA (study level meta-analysis) -#' @details glmerSLMADS2 is a serverside function called by ds.glmerSLMA on the clientside. +#' @details glmerSLMA2DS is a serverside function called by ds.glmerSLMA on the clientside. #' The analytic work engine is the glmer function in R which sits in the lme4 package. #' ds.glmerSLMA fits a generalized linear mixed effects model (glme) - e.g. a logistic or #' Poisson regression model including both fixed and random effects - on data @@ -38,7 +38,7 @@ #' @author Tom Bishop, with some additions by Paul Burton #' @author Tim Cadman, Genomics Coordination Centre, UMCG, Netherlands #' @export -glmerSLMADS2 <- function(formula, offset, weights, dataName, family, +glmerSLMA2DS <- function(formula, offset, weights, dataName, family, control_type=NULL, control_value.transmit=NULL, nAGQ=1L, verbose = 0, theta = NULL, fixef = NULL){ errorMessage <- "No errors" @@ -445,4 +445,4 @@ if(control_type=="check.conv.grad") } # AGGREGATE FUNCTION -# glmerSLMADS2 +# glmerSLMA2DS diff --git a/R/glmerSLMADS.assign.R b/R/glmerSLMADS.assign.R index 36c7159c..11088f17 100644 --- a/R/glmerSLMADS.assign.R +++ b/R/glmerSLMADS.assign.R @@ -1,5 +1,5 @@ #' @title Fitting generalized linear mixed effect models - serverside function -#' @description glmerSLMADS.assign is the same as glmerSLMADS2 which fits a generalized linear +#' @description glmerSLMADS.assign is the same as glmerSLMA2DS which fits a generalized linear #' mixed effects model (glme) per study and saves the outcomes in each study #' @details glmerSLMADS.assign is a serverside function called by ds.glmerSLMA on the clientside. #' The analytic work engine is the glmer function in R which sits in the lme4 package. diff --git a/R/histogramDS1.R b/R/histogram1DS.R similarity index 97% rename from R/histogramDS1.R rename to R/histogram1DS.R index 97e09780..9bc5137e 100644 --- a/R/histogramDS1.R +++ b/R/histogram1DS.R @@ -22,7 +22,7 @@ #' @author Tim Cadman, Genomics Coordination Centre, UMCG, Netherlands #' @export #' -histogramDS1 <- function(x, method.indicator, k, noise){ +histogram1DS <- function(x, method.indicator, k, noise){ xvect <- .loadServersideObject(x) .checkClass(obj = xvect, obj_name = x, permitted_classes = c("numeric", "integer")) @@ -53,7 +53,7 @@ histogramDS1 <- function(x, method.indicator, k, noise){ # the study-specific seed for random number generation seed <- getOption("datashield.seed") if (is.null(seed)) - stop("histogramDS1 requires 'datashield.seed' R option to operate", call.=FALSE) + stop("histogram1DS requires 'datashield.seed' R option to operate", call.=FALSE) set.seed(seed) rr <- c(min(xvect, na.rm=TRUE), max(xvect, na.rm=TRUE)) @@ -147,4 +147,4 @@ histogramDS1 <- function(x, method.indicator, k, noise){ } # AGGREGATE FUNCTION -# histogramDS1 +# histogram1DS diff --git a/R/histogramDS2.R b/R/histogram2DS.R similarity index 99% rename from R/histogramDS2.R rename to R/histogram2DS.R index 4e85b83f..f70bb46c 100644 --- a/R/histogramDS2.R +++ b/R/histogram2DS.R @@ -23,7 +23,7 @@ #' @author Tim Cadman, Genomics Coordination Centre, UMCG, Netherlands #' @export #' -histogramDS2 <- function (x, num.breaks, min, max, method.indicator, k, noise){ +histogram2DS <- function (x, num.breaks, min, max, method.indicator, k, noise){ xvect <- .loadServersideObject(x) .checkClass(obj = xvect, obj_name = x, permitted_classes = c("numeric", "integer")) @@ -177,4 +177,4 @@ histogramDS2 <- function (x, num.breaks, min, max, method.indicator, k, noise){ } # AGGREGATE FUNCTION -# histogramDS2 +# histogram2DS diff --git a/R/kurtosisDS1.R b/R/kurtosis1DS.R similarity index 97% rename from R/kurtosisDS1.R rename to R/kurtosis1DS.R index a51caa43..7ca858bd 100644 --- a/R/kurtosisDS1.R +++ b/R/kurtosis1DS.R @@ -12,7 +12,7 @@ #' @author Tim Cadman, Genomics Coordination Centre, UMCG, Netherlands #' @export #' -kurtosisDS1 <- function (x, method){ +kurtosis1DS <- function (x, method){ ############################################################# # MODULE 1: CAPTURE THE nfilter SETTINGS @@ -48,4 +48,4 @@ kurtosisDS1 <- function (x, method){ } #AGGREGATE FUNCTION -# kurtosisDS1 +# kurtosis1DS diff --git a/R/kurtosisDS2.R b/R/kurtosis2DS.R similarity index 97% rename from R/kurtosisDS2.R rename to R/kurtosis2DS.R index e7790329..23ea2cf8 100644 --- a/R/kurtosisDS2.R +++ b/R/kurtosis2DS.R @@ -15,7 +15,7 @@ #' @author Tim Cadman, Genomics Coordination Centre, UMCG, Netherlands #' @export #' -kurtosisDS2 <- function(x, global.mean){ +kurtosis2DS <- function(x, global.mean){ ############################################################# # MODULE 1: CAPTURE THE nfilter SETTINGS @@ -39,4 +39,4 @@ kurtosisDS2 <- function(x, global.mean){ } #AGGREGATE FUNCTION -# kurtosisDS2 +# kurtosis2DS diff --git a/R/lexisDS1.R b/R/lexis1DS.R similarity index 95% rename from R/lexisDS1.R rename to R/lexis1DS.R index 45bea015..7ebaf90f 100644 --- a/R/lexisDS1.R +++ b/R/lexis1DS.R @@ -1,5 +1,5 @@ #' -#' @title lexisDS1 +#' @title lexis1DS #' #' @description The first server-side function called by ds.lexis. #' @details This is an aggregate function. @@ -12,7 +12,7 @@ #' @return List with `max.time` #' @export #' -lexisDS1 <- function(exitCol=NULL){ +lexis1DS <- function(exitCol=NULL){ ############################################################# #MODULE 1: CAPTURE THE nfilter SETTINGS @@ -42,4 +42,4 @@ lexisDS1 <- function(exitCol=NULL){ } #AGGREGATE FUNCTION -# lexisDS1 +# lexis1DS diff --git a/R/lexisDS2.R b/R/lexis2DS.R similarity index 98% rename from R/lexisDS2.R rename to R/lexis2DS.R index d4366720..f6a33004 100644 --- a/R/lexisDS2.R +++ b/R/lexis2DS.R @@ -1,10 +1,10 @@ #' -#' @title lexisDS2 +#' @title lexis2DS #' @description The second serverside function called by ds.lexis. #' @details This is the assign #' function which actually creates #' the expanded dataframe containing survival data for a piecewise exponential -#' regression. lexisDS2 also +#' regression. lexis2DS also #' carries out a series of disclosure checks and if the arguments or data fail any of #' those tests, #' creation of the expanded dataframe is blocked and an appropriate serverside error @@ -36,7 +36,7 @@ #' @return List with `expanded.table` #' @export #' -lexisDS2 <- function(datatext=NULL, intervalWidth, maxmaxtime, idCol, entryCol, exitCol, statusCol, vartext=NULL){ +lexis2DS <- function(datatext=NULL, intervalWidth, maxmaxtime, idCol, entryCol, exitCol, statusCol, vartext=NULL){ ############################################################# #MODULE 1: CAPTURE THE nfilter SETTINGS @@ -217,7 +217,7 @@ lexisDS2 <- function(datatext=NULL, intervalWidth, maxmaxtime, idCol, entryCol, idSeq.matrix<-matrix(0,totsubs,totints) - #ERROR IN ORIGINAL lexisDS2 CORRECTED + #ERROR IN ORIGINAL lexis2DS CORRECTED ###ERR numperiods.exposed<-rep(0,totsubs) first.int.exposed<-rep(1,totsubs) @@ -316,4 +316,4 @@ lexisDS2 <- function(datatext=NULL, intervalWidth, maxmaxtime, idCol, entryCol, } #ASSIGN FUNCTION -# lexisDS2 +# lexis2DS diff --git a/R/lexisDS3.R b/R/lexis3DS.R similarity index 71% rename from R/lexisDS3.R rename to R/lexis3DS.R index 75a31906..409f4270 100644 --- a/R/lexisDS3.R +++ b/R/lexis3DS.R @@ -1,18 +1,18 @@ #' #' @title -#' lexisDS3 +#' lexis3DS #' #' @description #' The third serverside function called by ds.lexis. #' @details This is an assign function that simplifies the -#' returned output from ds.lexis. Specifically, without lexisDS3 the output consists of a table within -#' a list, but lexisDS3 converts this directly into a dataframe. +#' returned output from ds.lexis. Specifically, without lexis3DS the output consists of a table within +#' a list, but lexis3DS converts this directly into a dataframe. #' For more details see the extensive header for ds.lexis. #' #' @return Data frame with `messageobj` object #' @export #' -lexisDS3 <- function(){ +lexis3DS <- function(){ outobj <- data.frame(base::get("messageobj", envir = parent.frame())$expanded.table) @@ -20,4 +20,4 @@ lexisDS3 <- function(){ } #ASSIGN FUNCTION -# lexisDS3 +# lexis3DS diff --git a/R/lmerSLMADS2.R b/R/lmerSLMA2DS.R similarity index 98% rename from R/lmerSLMADS2.R rename to R/lmerSLMA2DS.R index 7a1142d1..e962fba4 100644 --- a/R/lmerSLMADS2.R +++ b/R/lmerSLMA2DS.R @@ -1,8 +1,8 @@ #' @title Fitting linear mixed effect models - serverside function -#' @description lmerSLMADS2 is a serverside function which fits a linear mixed +#' @description lmerSLMA2DS is a serverside function which fits a linear mixed #' effects model (lme) - i.e. can include both fixed and random effects - on data from #' one or multiple sources with pooling via SLMA (study level meta-analysis) -#' @details lmerSLMADS2 is a serverside function called by ds.lmerSLMA on the clientside. +#' @details lmerSLMA2DS is a serverside function called by ds.lmerSLMA on the clientside. #' The analytic work engine is the lmer function in R which sits in the lme4 package. #' ds.lmerSLMA fits a linear mixed effects model (lme) - can include both fixed and random #' effects - on data from a single or multiple sources. When there are multiple data sources, @@ -12,7 +12,7 @@ #' using the metafor package, but as the SLMA occurs on the clientside which, as far #' as the user is concerned is just a standard R environment, the user can choose to use #' any approach to meta-analysis they choose. For more detailed help about any aspect -#' of lmerSLMDS2 please see the extensive help for ds.lmerSLMA. Additional information +#' of lmerSLM2DS please see the extensive help for ds.lmerSLMA. Additional information #' about fitting lmes using the lmer engine can be obtained using R help for lmer and #' the lme4 package #' @param formula see help for ds.lmerSLMA @@ -29,7 +29,7 @@ #' @author Tom Bishop, with some additions by Paul Burton #' @author Tim Cadman, Genomics Coordination Centre, UMCG, Netherlands #' @export -lmerSLMADS2 <- function(formula, offset, weights, dataName, REML = TRUE, +lmerSLMA2DS <- function(formula, offset, weights, dataName, REML = TRUE, control_type, control_value.transmit, optimizer, verbose=0){ errorMessage <- "No errors" @@ -435,4 +435,4 @@ if(!is.null(optimizer)&&optimizer!="nloptwrap") } # AGGREGATE FUNCTION -# lmerSLMADS2 +# lmerSLMA2DS diff --git a/R/lmerSLMADS.assign.R b/R/lmerSLMADS.assign.R index 7731c552..ab732ae7 100644 --- a/R/lmerSLMADS.assign.R +++ b/R/lmerSLMADS.assign.R @@ -1,5 +1,5 @@ #' @title Fitting linear mixed effect models - serverside function -#' @description lmerSLMADS.assign is the same as lmerSLMADS2 which fits a linear +#' @description lmerSLMADS.assign is the same as lmerSLMA2DS which fits a linear #' mixed effects model (lme) per study and saves the outcomes in each study #' @details lmerSLMADS.assign is a serverside function called by ds.lmerSLMA on the clientside. #' The analytic work engine is the lmer function in R which sits in the lme4 package. diff --git a/R/matrixDetDS1.R b/R/matrixDet1DS.R similarity index 96% rename from R/matrixDetDS1.R rename to R/matrixDet1DS.R index b6fb40ce..f647589e 100644 --- a/R/matrixDetDS1.R +++ b/R/matrixDet1DS.R @@ -14,7 +14,7 @@ #' @author Tim Cadman, Genomics Coordination Centre, UMCG, Netherlands #' @export -matrixDetDS1 <- function(M1.name=NULL,logarithm){ +matrixDet1DS <- function(M1.name=NULL,logarithm){ dsBase::checkPermissivePrivacyControlLevel(c('permissive', 'avocado', 'banana')) @@ -53,4 +53,4 @@ return(list(matrix.determinant=output)) } #AGGREGATE FUNCTION -# matrixDetDS1 +# matrixDet1DS diff --git a/R/matrixDetDS2.R b/R/matrixDet2DS.R similarity index 95% rename from R/matrixDetDS2.R rename to R/matrixDet2DS.R index 6e15e7d8..36b3d1df 100644 --- a/R/matrixDetDS2.R +++ b/R/matrixDet2DS.R @@ -14,7 +14,7 @@ #' @author Tim Cadman, Genomics Coordination Centre, UMCG, Netherlands #' @export -matrixDetDS2 <- function(M1.name=NULL,logarithm){ +matrixDet2DS <- function(M1.name=NULL,logarithm){ M1 <- .loadServersideObject(M1.name) .checkClass(obj = M1, obj_name = M1.name, permitted_classes = c("matrix", "data.frame")) @@ -42,4 +42,4 @@ return(output) } #ASSIGN FUNCTION -# matrixDetDS2 +# matrixDet2DS diff --git a/R/skewnessDS1.R b/R/skewness1DS.R similarity index 97% rename from R/skewnessDS1.R rename to R/skewness1DS.R index 64375375..5ae11dd1 100644 --- a/R/skewnessDS1.R +++ b/R/skewness1DS.R @@ -12,7 +12,7 @@ #' @author Tim Cadman, Genomics Coordination Centre, UMCG, Netherlands #' @export #' -skewnessDS1 <- function(x, method){ +skewness1DS <- function(x, method){ ############################################################# # MODULE 1: CAPTURE THE nfilter SETTINGS @@ -48,5 +48,5 @@ skewnessDS1 <- function(x, method){ } #AGGREGATE FUNCTION -# skewnessDS1 +# skewness1DS diff --git a/R/skewnessDS2.R b/R/skewness2DS.R similarity index 97% rename from R/skewnessDS2.R rename to R/skewness2DS.R index aad3088d..75554111 100644 --- a/R/skewnessDS2.R +++ b/R/skewness2DS.R @@ -15,7 +15,7 @@ #' @author Tim Cadman, Genomics Coordination Centre, UMCG, Netherlands #' @export #' -skewnessDS2 <- function(x, global.mean){ +skewness2DS <- function(x, global.mean){ ############################################################# # MODULE 1: CAPTURE THE nfilter SETTINGS @@ -39,4 +39,4 @@ skewnessDS2 <- function(x, global.mean){ } #AGGREGATE FUNCTION -# skewnessDS2 +# skewness2DS diff --git a/R/tableDS2.R b/R/table2DS.R similarity index 97% rename from R/tableDS2.R rename to R/table2DS.R index 81886679..878d0b47 100644 --- a/R/tableDS2.R +++ b/R/table2DS.R @@ -30,7 +30,7 @@ #' @author Paul Burton for DataSHIELD Development Team, 13/11/2019 #' @author Tim Cadman, Genomics Coordination Centre, UMCG, Netherlands #' @export -tableDS2 <- function(newobj,rvar.transmit,cvar.transmit,stvar.transmit){ +table2DS <- function(newobj,rvar.transmit,cvar.transmit,stvar.transmit){ table.obj <- .loadServersideObject(newobj) @@ -64,4 +64,4 @@ return(out.list) } #AGGREGATE FUNCTION -# tableDS2 +# table2DS diff --git a/docs/404.html b/docs/404.html index 17940f30..ae004152 100644 --- a/docs/404.html +++ b/docs/404.html @@ -1,8 +1,7 @@ - - + Page not found (404) • dsBase @@ -20,7 +19,7 @@ dsBase - 6.3.6.9000 + 7.0.0.9000 - - - - - -
-
-
- -

Secure ranking of "V2BR" (vector to be ranked) across all sources

- -
blackBoxDS.Rd
-
- -
-

The first key serverside function that sets up the V2BR for -ranking in the client.

-
- -
-

Usage

- 
blackBoxDS(input.var.name = NULL, shared.seedval, synth.real.ratio, NA.manage)
-
- -
-

Arguments

- - -
input.var.name
-

a character string specifying the name of V2BR. This -argument is set by the argument with the same name in the clientside function -ds.ranksSecure

- - -
shared.seedval
-

a pseudorandom number seed that ensures that the -processes generating the order and parameterisation of the encryption -algorithms are the same in each study. This argument is set by the argument -<shared.seed.value> in the clientside function ds.ranksSecure. For more -details, including future plans to share this starting seed in a more secure -way, please see the associated document entitled "secure.global.ranking.docx" -and the header file for ds.ranksSecure.

- - -
synth.real.ratio
-

an integer value representing -the ratio of synthetic (pseudo-data) values to the real number of -values in V2BR. This argument is set by the argument with the same name -in the clientside function ds.ranksSecure. For more details, please see the -associated document entitled "secure.global.ranking.docx" and the header file -for ds.ranksSecure.

- - -
NA.manage
-

character string indicating how missing values (NAs) in -V2BR should be managed. It takes three possible values: "NA.delete", -"NA.low","NA.hi". This argument is set by the argument with the same name -in the clientside function ds.ranksSecure. For more details, please see the -associated document entitled "secure.global.ranking.docx" and the header file -for ds.ranksSecure.

- -
-
-

Value

-

writes a data frame object entitled blackbox.output.df to the -serverside. In each study this contains the encrypted -"combined real+pseudo data vector" and a range of other key components -from the first stage of the ranking procedure. For more details see the -associated document entitled "secure.global.ranking.docx"

-
-
-

Details

-

Severside assign function called by ds.ranksSecure. -Creates pseudo-data by using the real distribution of values in V2BR -to create a large number of synthetic data with a similar distribution to -the values in V2BR but with a slightly broader distribution at both ends -to ensure that any extreme values in the "combined real+pseudo data vector" -are all pseudo-data. Also ensures that the number of decimal places of -the values in the V2BR is reflected by the number of decimal places in -the pseudodata. Finally, takes the "combined real+pseudo data vector" through -seven rounds of rank consistent encryption that involves algorithms -themselves generated by a pseudorandom process that selects which -transformation to apply and with what parameters. The encryption algorithms -are the same in each study ensuring that ranks also remain consistent between -studies. After encryption the encrypted "combined real+pseudo data vector" is -written to the serverside as a dataframe also including other key component -vectors from the first stage of the ranking procedure. -For more details about the cluster of functions that -collectively enable secure global ranking and estimation of global quantiles -see the associated document entitled "secure.global.ranking.docx". Also -see the header file for ds.ranksSecure

-
-
-

Author

-

Paul Burton 9th November, 2021

-
- -
- - -
-

Developed by Paul Burton, Rebecca Wilson, Olly Butters, Patricia Ryser-Welch, Alex Westerberg, Leire Abarrategui, Roberto Villegas-Diaz, Demetris Avraam, Yannick Marcon, Tom Bishop, Amadou Gaye, Xavier Escribà-Montagut, Stuart Wheater.

-
- -
-

Site built with pkgdown 2.2.0.

-
- -
- - - - - - - diff --git a/docs/reference/blackBoxDS.md b/docs/reference/blackBoxDS.md deleted file mode 100644 index 5261428c..00000000 --- a/docs/reference/blackBoxDS.md +++ /dev/null @@ -1,81 +0,0 @@ -# Secure ranking of "V2BR" (vector to be ranked) across all sources - -The first key serverside function that sets up the V2BR for ranking in -the client. - -## Usage - -``` r -blackBoxDS(input.var.name = NULL, shared.seedval, synth.real.ratio, NA.manage) -``` - -## Arguments - -- input.var.name: - - a character string specifying the name of V2BR. This argument is set - by the argument with the same name in the clientside function - ds.ranksSecure - -- shared.seedval: - - a pseudorandom number seed that ensures that the processes generating - the order and parameterisation of the encryption algorithms are the - same in each study. This argument is set by the argument - \ in the clientside function ds.ranksSecure. For - more details, including future plans to share this starting seed in a - more secure way, please see the associated document entitled - "secure.global.ranking.docx" and the header file for ds.ranksSecure. - -- synth.real.ratio: - - an integer value representing the ratio of synthetic (pseudo-data) - values to the real number of values in V2BR. This argument is set by - the argument with the same name in the clientside function - ds.ranksSecure. For more details, please see the associated document - entitled "secure.global.ranking.docx" and the header file for - ds.ranksSecure. - -- NA.manage: - - character string indicating how missing values (NAs) in V2BR should be - managed. It takes three possible values: "NA.delete", - "NA.low","NA.hi". This argument is set by the argument with the same - name in the clientside function ds.ranksSecure. For more details, - please see the associated document entitled - "secure.global.ranking.docx" and the header file for ds.ranksSecure. - -## Value - -writes a data frame object entitled blackbox.output.df to the -serverside. In each study this contains the encrypted "combined -real+pseudo data vector" and a range of other key components from the -first stage of the ranking procedure. For more details see the -associated document entitled "secure.global.ranking.docx" - -## Details - -Severside assign function called by ds.ranksSecure. Creates pseudo-data -by using the real distribution of values in V2BR to create a large -number of synthetic data with a similar distribution to the values in -V2BR but with a slightly broader distribution at both ends to ensure -that any extreme values in the "combined real+pseudo data vector" are -all pseudo-data. Also ensures that the number of decimal places of the -values in the V2BR is reflected by the number of decimal places in the -pseudodata. Finally, takes the "combined real+pseudo data vector" -through seven rounds of rank consistent encryption that involves -algorithms themselves generated by a pseudorandom process that selects -which transformation to apply and with what parameters. The encryption -algorithms are the same in each study ensuring that ranks also remain -consistent between studies. After encryption the encrypted "combined -real+pseudo data vector" is written to the serverside as a dataframe -also including other key component vectors from the first stage of the -ranking procedure. For more details about the cluster of functions that -collectively enable secure global ranking and estimation of global -quantiles see the associated document entitled -"secure.global.ranking.docx". Also see the header file for -ds.ranksSecure - -## Author - -Paul Burton 9th November, 2021 diff --git a/docs/reference/blackBoxRanksDS.html b/docs/reference/blackBoxRanksDS.html deleted file mode 100644 index dbf3c955..00000000 --- a/docs/reference/blackBoxRanksDS.html +++ /dev/null @@ -1,132 +0,0 @@ - -Secure ranking of "V2BR" (vector to be ranked) across all sources — blackBoxRanksDS • dsBase - Skip to contents - - -
-
-
- -

Secure ranking of "V2BR" (vector to be ranked) across all sources

- -
blackBoxRanksDS.Rd
-
- -
-

The second key serverside function that prepares the global -ranks of the the real data only generated in the first stage of the -ranking procedure and encrypts them in preparation for generating global -ranks that correspond 1 to 1 with only the real data in V2BR.

-
- -
-

Usage

- 
blackBoxRanksDS(input.var.name = NULL, shared.seedval)
-
- -
-

Arguments

- - -
input.var.name
-

a character string specifying the name of the -vector holding the global ranks. This argument is set automatically by -the clientside function ds.ranksSecure

- - -
shared.seedval
-

a pseudorandom number seed that ensures that the -processes generating the order and parameterisation of the encryption -algorithms are the same in each study. This argument is set by the argument -<shared.seed.value> in the clientside function ds.ranksSecure. The -seed value shared by all studies in setting up the encryption procedures -in blackBoxRanksDS is arbitrarily changed from that used to set up the -encryption procedures in blackBoxDS, so the the set of 7 encryption -algorithms is deliberately different. For more -details, including future plans to share this starting seed in a more secure -way, please see the associated document entitled "secure.global.ranking.docx" -and the header file for ds.ranksSecure.

- -
-
-

Value

-

writes a data frame object entitled blackbox.ranks.df to the -serverside. In each study this contains the encrypted global ranks -and a range of other key components from the second stage (ranking of global -ranks for real observations only) of the ranking procedure. For more details -see the associated document entitled "secure.global.ranking.docx"

-
-
-

Details

-

Severside assign function called by ds.ranksSecure. It takes the -global ranks currently held in sR5.df which reflect the global ranks based on -the "combined real+pseudo data vector" as encrypted by blackBoxDS -but with all pseudo-data stripped out. It then uses these global ranks (of -the real data) as if they were a new variable to be ranked. This is then -equivalent to blackBoxDS with the primary difference that no -pseudo-data are needed. This is because the global ranks are fundamentally -non-disclosive and so can be transferred to the clientside with no risk of -disclosure. However, in order to ensure that the client cannot compare -the list of global.ranks in sR4.df (after initial global ranking based on -ranking of real and pseudo-data combined) with the global.ranks to be -generated by blackBoxRanksDS (based solely on the real data they are -processed through seven more rounds of encryption as before in blackBoxDS. -In consequence the client remains unable to determine which of the original -global ranks corresponded to real data and which to pseudo-data. In -addition, blackBoxRanksDS does not need to determine the number of decimal -places in the data because it is only applied to ranks which are assumed to -be integers. For more details about the cluster of functions that -collectively enable secure global ranking and estimation of global quantiles -see the associated document entitled "secure.global.ranking.docx". Also -see the header file for ds.ranksSecure and the header file for blackBoxDS

-
-
-

Author

-

Paul Burton 9th November, 2021

-
- -
- - -
-

Developed by Paul Burton, Rebecca Wilson, Olly Butters, Patricia Ryser-Welch, Alex Westerberg, Leire Abarrategui, Roberto Villegas-Diaz, Demetris Avraam, Yannick Marcon, Tom Bishop, Amadou Gaye, Xavier Escribà-Montagut, Stuart Wheater.

-
- -
-

Site built with pkgdown 2.2.0.

-
- -
- - - - - - - diff --git a/docs/reference/blackBoxRanksDS.md b/docs/reference/blackBoxRanksDS.md deleted file mode 100644 index 5634fd90..00000000 --- a/docs/reference/blackBoxRanksDS.md +++ /dev/null @@ -1,71 +0,0 @@ -# Secure ranking of "V2BR" (vector to be ranked) across all sources - -The second key serverside function that prepares the global ranks of the -the real data only generated in the first stage of the ranking procedure -and encrypts them in preparation for generating global ranks that -correspond 1 to 1 with only the real data in V2BR. - -## Usage - -``` r -blackBoxRanksDS(input.var.name = NULL, shared.seedval) -``` - -## Arguments - -- input.var.name: - - a character string specifying the name of the vector holding the - global ranks. This argument is set automatically by the clientside - function ds.ranksSecure - -- shared.seedval: - - a pseudorandom number seed that ensures that the processes generating - the order and parameterisation of the encryption algorithms are the - same in each study. This argument is set by the argument - \ in the clientside function ds.ranksSecure. The - seed value shared by all studies in setting up the encryption - procedures in blackBoxRanksDS is arbitrarily changed from that used to - set up the encryption procedures in blackBoxDS, so the the set of 7 - encryption algorithms is deliberately different. For more details, - including future plans to share this starting seed in a more secure - way, please see the associated document entitled - "secure.global.ranking.docx" and the header file for ds.ranksSecure. - -## Value - -writes a data frame object entitled blackbox.ranks.df to the serverside. -In each study this contains the encrypted global ranks and a range of -other key components from the second stage (ranking of global ranks for -real observations only) of the ranking procedure. For more details see -the associated document entitled "secure.global.ranking.docx" - -## Details - -Severside assign function called by ds.ranksSecure. It takes the global -ranks currently held in sR5.df which reflect the global ranks based on -the "combined real+pseudo data vector" as encrypted by blackBoxDS but -with all pseudo-data stripped out. It then uses these global ranks (of -the real data) as if they were a new variable to be ranked. This is then -equivalent to blackBoxDS with the primary difference that no pseudo-data -are needed. This is because the global ranks are fundamentally -non-disclosive and so can be transferred to the clientside with no risk -of disclosure. However, in order to ensure that the client cannot -compare the list of global.ranks in sR4.df (after initial global ranking -based on ranking of real and pseudo-data combined) with the global.ranks -to be generated by blackBoxRanksDS (based solely on the real data they -are processed through seven more rounds of encryption as before in -blackBoxDS. In consequence the client remains unable to determine which -of the original global ranks corresponded to real data and which to -pseudo-data. In addition, blackBoxRanksDS does not need to determine the -number of decimal places in the data because it is only applied to ranks -which are assumed to be integers. For more details about the cluster of -functions that collectively enable secure global ranking and estimation -of global quantiles see the associated document entitled -"secure.global.ranking.docx". Also see the header file for -ds.ranksSecure and the header file for blackBoxDS - -## Author - -Paul Burton 9th November, 2021 diff --git a/docs/reference/booleDS.html b/docs/reference/booleDS.html new file mode 100644 index 00000000..ca1a5b0b --- /dev/null +++ b/docs/reference/booleDS.html @@ -0,0 +1,120 @@ + +booleDS — booleDS • dsBase + Skip to contents + + +
+
+
+ +

booleDS

+ +
booleDS.Rd
+
+ +
+

Converts the individual elements of a vector or other object into +Boolean indicators.

+
+ +
+

Usage

+ 
booleDS(
+  V1.name = NULL,
+  V2.name = NULL,
+  Boolean.operator.n = NULL,
+  na.assign.text,
+  numeric.output = TRUE
+)
+
+ +
+

Arguments

+ + +
V1.name
+

A character string specifying the name of the vector to which the +Boolean operator is to be applied

+ + +
V2.name
+

A character string specifying the name of the vector or scalar to +which <V1> is to be compared.

+ + +
Boolean.operator.n
+

An integer value (1 to 6) providing a numeric coding for +the character string +specifying one of six possible Boolean operators: '==', '!=', '>', '>=','<', '<=' +that could legally be passed +from client to server via DataSHIELD parser

+ + +
na.assign.text
+

A character string taking values 'NA', '1' or '0'. If 'NA' +then any NA values in the +input vector remain as NAs in the output vector. If '1' or '0' NA values in the +input vector are all converted to 1 or 0 respectively.

+ + +
numeric.output
+

a TRUE/FALSE indicator defaulting to TRUE determining whether +the final output variable +should be of class numeric (1/0) or class logical (TRUE/FALSE).

+ +
+
+

Value

+

the levels of the input variable.

+
+
+

Details

+

The function converts the input vector into Boolean indicators.

+
+
+

Author

+

DataSHIELD Development Team

+

Tim Cadman, Genomics Coordination Centre, UMCG, Netherlands

+
+ +
+ + +
+

Developed by Paul Burton, Rebecca Wilson, Olly Butters, Patricia Ryser-Welch, Alex Westerberg, Leire Abarrategui, Roberto Villegas-Diaz, Demetris Avraam, Yannick Marcon, Tom Bishop, Amadou Gaye, Xavier Escribà-Montagut, Stuart Wheater.

+
+ +
+

Site built with pkgdown 2.2.1.

+
+ +
+ + + + + + + diff --git a/docs/reference/booleDS.md b/docs/reference/booleDS.md new file mode 100644 index 00000000..39c81779 --- /dev/null +++ b/docs/reference/booleDS.md @@ -0,0 +1,62 @@ +# booleDS + +Converts the individual elements of a vector or other object into +Boolean indicators. + +## Usage + +``` r +booleDS( + V1.name = NULL, + V2.name = NULL, + Boolean.operator.n = NULL, + na.assign.text, + numeric.output = TRUE +) +``` + +## Arguments + +- V1.name: + + A character string specifying the name of the vector to which the + Boolean operator is to be applied + +- V2.name: + + A character string specifying the name of the vector or scalar to + which \ is to be compared. + +- Boolean.operator.n: + + An integer value (1 to 6) providing a numeric coding for the character + string specifying one of six possible Boolean operators: '==', '!=', + '\>', '\>=','\<', '\<=' that could legally be passed from client to + server via DataSHIELD parser + +- na.assign.text: + + A character string taking values 'NA', '1' or '0'. If 'NA' then any NA + values in the input vector remain as NAs in the output vector. If '1' + or '0' NA values in the input vector are all converted to 1 or 0 + respectively. + +- numeric.output: + + a TRUE/FALSE indicator defaulting to TRUE determining whether the + final output variable should be of class numeric (1/0) or class + logical (TRUE/FALSE). + +## Value + +the levels of the input variable. + +## Details + +The function converts the input vector into Boolean indicators. + +## Author + +DataSHIELD Development Team + +Tim Cadman, Genomics Coordination Centre, UMCG, Netherlands diff --git a/docs/reference/boxPlotGGDS.html b/docs/reference/boxPlotGGDS.html index ed19da2e..5d8056c2 100644 --- a/docs/reference/boxPlotGGDS.html +++ b/docs/reference/boxPlotGGDS.html @@ -1,5 +1,5 @@ -Create the identity stats and necessary data to draw a plot on the client — boxPlotGGDS • dsBaseCreate the identity stats and necessary data to draw a plot on the client — boxPlotGGDS • dsBasedsBase - 6.3.6.9000 + 7.0.0.9000 - - dsBase - 6.3.3 - - - - - - - - - -
-
-
-

Splits character by '$' and returns the single characters

- - -
- -
-

This is an internal function.

-
- -
- 
extract(input)
-
- -
-

Arguments

- - -
input
-

a vector or a list of characters

- -
-
-

Value

-

a vector of characters

-
-
-

Details

-

Not required

-
- -
- -
- - -
-

Developed by Paul Burton, Rebecca Wilson, Olly Butters, Patricia Ryser-Welch, Alex Westerberg, Leire Abarrategui, Roberto Villegas-Diaz, Demetris Avraam, Yannick Marcon, Stuart Wheater.

-
- -
-

Site built with pkgdown 2.1.3.

-
- -
- - - - - - - - diff --git a/docs/reference/extractQuantilesDS1.html b/docs/reference/extractQuantilesDS1.html deleted file mode 100644 index 757856e3..00000000 --- a/docs/reference/extractQuantilesDS1.html +++ /dev/null @@ -1,123 +0,0 @@ - -Secure ranking of "V2BR" (vector to be ranked) across all sources and use of these ranks to estimate global quantiles across all studies — extractQuantilesDS1 • dsBase - Skip to contents - - -
-
-
- -

Secure ranking of "V2BR" (vector to be ranked) across all sources and use of these ranks to estimate global quantiles across all studies

- -
extractQuantilesDS1.Rd
-
- -
-

identify the global values of V2BR (i.e. the values across all -studies) that relate to a set of quantiles to be evaluated.

-
- -
-

Usage

- 
extractQuantilesDS1(extract.quantiles, extract.summary.output.ranks.df)
-
- -
-

Arguments

- - -
extract.quantiles
-

one of a restricted set of character strings that -fix the set of quantile values for which the corresponding values across -all studies are to be estimated. For more details -see the associated document entitled "secure.global.ranking.docx", the -header for ds.ranksSecure and ds.extractQuantiles functions. -The value of this argument is set in choosing the value of the argument -<quantiles.for.estimation> in ds.ranksSecure.

- - -
extract.summary.output.ranks.df
-

character string specifying optional -name for the data.frame written to the serverside on each data source that -contains 5 of the key output variables from the ranking procedure pertaining -to that particular data source. This data frame represents the key source of -information - including global ranks - that determines the values of V2BR -that are identified as corresponding to the particular set of quantiles to -be estimated as specified by the <quantiles.for.estimation> argument of -function ds.ranksSecure (and the <extract.quantiles> argument of -ds.extractQuantiles).

- -
-
-

Value

-

as a first step in creating the vector of values of values of V2BR -that correspond to each quantile value, extractQuantilesDS1 identifies the -two closest quantile values across all studies that span each key quantile -value. These are saved as the data frame "closest.bounds.df" on the -clientside and then saved on the serverside by ds.dmtC2S into the data frame -"global.bounds.df". Also if the number of observations across all studies is -too small, and a disclosure risk exists if the final.quantile.vector is made -available via the client, this function stops the processing and returns a -warning/error message.

-
-
-

Details

-

Severside aggregate function called by ds.extractQuantiles via -ds.ranksSecure. As well as estimating the key values of V2BR that correspond -to the selected quantiles, this function also implements a disclosure control -trap. If the ratio of the total number of all observations across all studies -divided by the number of quantile values to be estimated is less than or -equal to nfilter.subset (which specifies the minimum size of a subset) the -process stops and an error message is returned suggesting that you might -try selecting a narrower range of quantiles with less quantile values to be -estimated as specified by the argument <quantiles.for.estimation> of the -function ds.ranksSecure. For more details about the cluster of functions that -collectively enable secure global ranking and estimation of global quantiles -see the associated document entitled "secure.global.ranking.docx"

-
-
-

Author

-

Paul Burton 11th November, 2021

-
- -
- - -
-

Developed by Paul Burton, Rebecca Wilson, Olly Butters, Patricia Ryser-Welch, Alex Westerberg, Leire Abarrategui, Roberto Villegas-Diaz, Demetris Avraam, Yannick Marcon, Tom Bishop, Amadou Gaye, Xavier Escribà-Montagut, Stuart Wheater.

-
- -
-

Site built with pkgdown 2.2.0.

-
- -
- - - - - - - diff --git a/docs/reference/extractQuantilesDS1.md b/docs/reference/extractQuantilesDS1.md deleted file mode 100644 index b828396a..00000000 --- a/docs/reference/extractQuantilesDS1.md +++ /dev/null @@ -1,66 +0,0 @@ -# Secure ranking of "V2BR" (vector to be ranked) across all sources and use of these ranks to estimate global quantiles across all studies - -identify the global values of V2BR (i.e. the values across all studies) -that relate to a set of quantiles to be evaluated. - -## Usage - -``` r -extractQuantilesDS1(extract.quantiles, extract.summary.output.ranks.df) -``` - -## Arguments - -- extract.quantiles: - - one of a restricted set of character strings that fix the set of - quantile values for which the corresponding values across all studies - are to be estimated. For more details see the associated document - entitled "secure.global.ranking.docx", the header for ds.ranksSecure - and ds.extractQuantiles functions. The value of this argument is set - in choosing the value of the argument \ in - ds.ranksSecure. - -- extract.summary.output.ranks.df: - - character string specifying optional name for the data.frame written - to the serverside on each data source that contains 5 of the key - output variables from the ranking procedure pertaining to that - particular data source. This data frame represents the key source of - information - including global ranks - that determines the values of - V2BR that are identified as corresponding to the particular set of - quantiles to be estimated as specified by the - \ argument of function ds.ranksSecure (and - the \ argument of ds.extractQuantiles). - -## Value - -as a first step in creating the vector of values of values of V2BR that -correspond to each quantile value, extractQuantilesDS1 identifies the -two closest quantile values across all studies that span each key -quantile value. These are saved as the data frame "closest.bounds.df" on -the clientside and then saved on the serverside by ds.dmtC2S into the -data frame "global.bounds.df". Also if the number of observations across -all studies is too small, and a disclosure risk exists if the -final.quantile.vector is made available via the client, this function -stops the processing and returns a warning/error message. - -## Details - -Severside aggregate function called by ds.extractQuantiles via -ds.ranksSecure. As well as estimating the key values of V2BR that -correspond to the selected quantiles, this function also implements a -disclosure control trap. If the ratio of the total number of all -observations across all studies divided by the number of quantile values -to be estimated is less than or equal to nfilter.subset (which specifies -the minimum size of a subset) the process stops and an error message is -returned suggesting that you might try selecting a narrower range of -quantiles with less quantile values to be estimated as specified by the -argument \ of the function ds.ranksSecure. -For more details about the cluster of functions that collectively enable -secure global ranking and estimation of global quantiles see the -associated document entitled "secure.global.ranking.docx" - -## Author - -Paul Burton 11th November, 2021 diff --git a/docs/reference/extractQuantilesDS2.html b/docs/reference/extractQuantilesDS2.html deleted file mode 100644 index e1d6d96c..00000000 --- a/docs/reference/extractQuantilesDS2.html +++ /dev/null @@ -1,121 +0,0 @@ - -Secure ranking of "V2BR" (vector to be ranked) across all sources and use of these ranks to estimate global quantiles across all studies — extractQuantilesDS2 • dsBase - Skip to contents - - -
-
-
- -

Secure ranking of "V2BR" (vector to be ranked) across all sources and use of these ranks to estimate global quantiles across all studies

- -
extractQuantilesDS2.Rd
-
- -
-

identify the global values of V2BR (i.e. the values across all -studies) that relate to a set of quantiles to be evaluated.

-
- -
-

Usage

- 
extractQuantilesDS2(extract.summary.output.ranks.df)
-
- -
-

Arguments

- - -
extract.summary.output.ranks.df
-

character string specifies an optional -name for the data.frame written to the serverside on each data source that -contains 5 of the key output variables from the ranking procedure pertaining -to that particular data source. This data frame represents the key source of -information - including global ranks - that determines the values of V2BR -that are identified as corresponding to the particular set of quantiles to -be estimated as specified by the <quantiles.for.estimation> argument of -function ds.ranksSecure (and the <extract.quantiles> argument of -ds.extractQuantiles).

- -
-
-

Value

-

the single value of V2BR which best corresponds to each key quantile -value to be estimated as specified by the argument <quantiles.for.estimation> -A data frame (final.quantile.df)summarising the results of this analysis -is written to the clientside. This data frame consists of two vectors. The -first is named "evaluation.quantiles". It lists the full set of quantiles -you have requested for evaluation as specified by the argument -"quantiles.for.estimation" The second vector which is called -"final.quantile.vector" details the values of V2BR that correspond to the -the key quantiles listed in vector 1.

-
-
-

Details

-

Severside aggregate function called by ds.extractQuantiles via -ds.ranksSecure. This takes the "global.bounds.df" data frame saved on the -serverside following construction by extractQuantilesDS1. This -data frame includes the two quantile values that most closely span each -quartile value to be estimated. If either of the values had been the correct -value for a given quantile, both the bounding values would have taken that -value in global.bounds.df. This is because the upper bound was defined as -the lowest value that was equal to or greater than the true value for that -quantile while the lower bound was defined as the highest value that was -equal to or lower than the true value. Next, the function extractQuantileDS2 -goes round study by study to identify the values of V2BR that actually -correspond to each of the spanning values around each quantile. Then the -function goes quantile by quantile and estimates the mean of the -two values of V2BR that correspond to the the spanning quantiles. If these -two values are the same it means that that value of V2BR is the -"true" value and the mean of two (or potentially several) instances of that -value is inevitably also equal to that true value. If the upper and lower -bounding values of V2BR differ, neither can be the precisely correct single -value of V2BR for that quantile (see above for explanation) and so the mean -of the two is a reasonable interpolated summary.

-
-
-

Author

-

Paul Burton 11th November, 2021

-
- -
- - -
-

Developed by Paul Burton, Rebecca Wilson, Olly Butters, Patricia Ryser-Welch, Alex Westerberg, Leire Abarrategui, Roberto Villegas-Diaz, Demetris Avraam, Yannick Marcon, Tom Bishop, Amadou Gaye, Xavier Escribà-Montagut, Stuart Wheater.

-
- -
-

Site built with pkgdown 2.2.0.

-
- -
- - - - - - - diff --git a/docs/reference/extractQuantilesDS2.md b/docs/reference/extractQuantilesDS2.md deleted file mode 100644 index 99e4e20a..00000000 --- a/docs/reference/extractQuantilesDS2.md +++ /dev/null @@ -1,65 +0,0 @@ -# Secure ranking of "V2BR" (vector to be ranked) across all sources and use of these ranks to estimate global quantiles across all studies - -identify the global values of V2BR (i.e. the values across all studies) -that relate to a set of quantiles to be evaluated. - -## Usage - -``` r -extractQuantilesDS2(extract.summary.output.ranks.df) -``` - -## Arguments - -- extract.summary.output.ranks.df: - - character string specifies an optional name for the data.frame written - to the serverside on each data source that contains 5 of the key - output variables from the ranking procedure pertaining to that - particular data source. This data frame represents the key source of - information - including global ranks - that determines the values of - V2BR that are identified as corresponding to the particular set of - quantiles to be estimated as specified by the - \ argument of function ds.ranksSecure (and - the \ argument of ds.extractQuantiles). - -## Value - -the single value of V2BR which best corresponds to each key quantile -value to be estimated as specified by the argument -\ A data frame (final.quantile.df)summarising -the results of this analysis is written to the clientside. This data -frame consists of two vectors. The first is named -"evaluation.quantiles". It lists the full set of quantiles you have -requested for evaluation as specified by the argument -"quantiles.for.estimation" The second vector which is called -"final.quantile.vector" details the values of V2BR that correspond to -the the key quantiles listed in vector 1. - -## Details - -Severside aggregate function called by ds.extractQuantiles via -ds.ranksSecure. This takes the "global.bounds.df" data frame saved on -the serverside following construction by extractQuantilesDS1. This data -frame includes the two quantile values that most closely span each -quartile value to be estimated. If either of the values had been the -correct value for a given quantile, both the bounding values would have -taken that value in global.bounds.df. This is because the upper bound -was defined as the lowest value that was equal to or greater than the -true value for that quantile while the lower bound was defined as the -highest value that was equal to or lower than the true value. Next, the -function extractQuantileDS2 goes round study by study to identify the -values of V2BR that actually correspond to each of the spanning values -around each quantile. Then the function goes quantile by quantile and -estimates the mean of the two values of V2BR that correspond to the the -spanning quantiles. If these two values are the same it means that that -value of V2BR is the "true" value and the mean of two (or potentially -several) instances of that value is inevitably also equal to that true -value. If the upper and lower bounding values of V2BR differ, neither -can be the precisely correct single value of V2BR for that quantile (see -above for explanation) and so the mean of the two is a reasonable -interpolated summary. - -## Author - -Paul Burton 11th November, 2021 diff --git a/docs/reference/fixClassDS.html b/docs/reference/fixClassDS.html index 35697eae..862ebd43 100644 --- a/docs/reference/fixClassDS.html +++ b/docs/reference/fixClassDS.html @@ -1,5 +1,5 @@ -Change Class of Target Variables in a Data Frame — fixClassDS • dsBase +Change Class of Target Variables in a Data Frame — fixClassDS • dsBase Skip to contents @@ -7,7 +7,7 @@ dsBase - 6.3.6.9000 + 7.0.0.9000 - - dsBase - 6.1.1 - - - - - - - - - - - -
-
-
-

Fitting generalized linear mixed effect models - serverside function

- - -
- -
-

glmerSLMADS.assing is the same as glmerSLMADS2 which fits a generalized linear -mixed effects model (glme) per study and saves the outcomes in each study

-
- - 
glmerSLMADS.assing(
-  formula,
-  offset,
-  weights,
-  dataName,
-  family,
-  control_type = NULL,
-  control_value.transmit = NULL,
-  nAGQ = 1L,
-  verbose = 0,
-  theta = NULL,
-  fixef = NULL
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
formula

see help for ds.glmerSLMA

offset

see help for ds.glmerSLMA

weights

see help for ds.glmerSLMA

dataName

see help for ds.glmerSLMA

family

see help for ds.glmerSLMA

control_type

see help for ds.glmerSLMA

control_value.transmit

see help for argument <control_value> for -function ds.glmerSLMA

nAGQ

integer scalar, defaulting to 1L. IN PRACTICE, IT MAY BE NECESSARY -TO SET nAGQ TO 0L when the model appears to converge perfectly well (e.g. verbose=2 -demonstrates good initial convergence of both the log-likelihood and -regression coefficients) but formal convergence does not get declared - -so no output is produced - despite running the model for many iterations. -The nAGQ argument is set by the nAGQ argument for ds.glmerSLMA and further -details can be found in help(ds.glmerSLMA) and in the native R help for glmer()

verbose

see help for ds.glmerSLMA

theta

see help for argument <start_theta> for -function ds.glmerSLMA

fixef

see help for argument <start_fixef> for -function ds.glmerSLMA

- -

Value

- -

writes glmerMod object summarising the fitted model to the serverside. -For more detailed information see help for ds.glmerSLMA.

-

Details

- -

glmerSLMADS.assign is a serverside function called by ds.glmerSLMA on the clientside. -The analytic work engine is the glmer function in R which sits in the lme4 package. -glmerSLMADS.assign fits a generalized linear mixed effects model (glme) - e.g. a logistic or -Poisson regression model including both fixed and random effects - on data -from each single data source and saves the regression outcomes on the serveside.

-

Author

- -

Demetris Avraam for DataSHIELD Development Team

- -
- -
- - -
-
-

Developed by DataSHIELD Developers.

-
- -
-

Site built with pkgdown 1.6.1.

-
- -
- - - - - - - - - diff --git a/docs/reference/heatmapPlotDS.html b/docs/reference/heatmapPlotDS.html index 6a5f6f19..c60f18df 100644 --- a/docs/reference/heatmapPlotDS.html +++ b/docs/reference/heatmapPlotDS.html @@ -1,5 +1,5 @@ -Calculates the coordinates of the centroid of each n nearest neighbours — heatmapPlotDS • dsBase +Calculates the coordinates of the centroid of each n nearest neighbours — heatmapPlotDS • dsBase Skip to contents @@ -7,7 +7,7 @@ dsBase - 6.3.6.9000 + 7.0.0.9000 + + + + + +
+
+
+ +

Computes the logarithm values of the input variable

+ +
logDS.Rd
+
+ +
+

This function is similar to R function log.

+
+ +
+

Usage

+ 
logDS(x, base = exp(1))
+
+ +
+

Arguments

+ + +
x
+

a string character, the name of a numeric or integer vector

+ + +
base
+

a positive number, the base for which logarithms are computed. +Default exp(1).

+ +
+
+

Value

+

the object specified by the newobj argument +of ds.log (or default name log.newobj) +which is written to the serverside. The output object is of class numeric.

+
+
+

Details

+

The function computes the logarithm values of an input numeric +or integer vector. By default natural logarithms are computed.

+
+
+

Author

+

DataSHIELD Development Team

+

Tim Cadman, Genomics Coordination Centre, UMCG, Netherlands

+
+ +
+ + +
+

Developed by Paul Burton, Rebecca Wilson, Olly Butters, Patricia Ryser-Welch, Alex Westerberg, Leire Abarrategui, Roberto Villegas-Diaz, Demetris Avraam, Yannick Marcon, Tom Bishop, Amadou Gaye, Xavier Escribà-Montagut, Stuart Wheater.

+
+ +
+

Site built with pkgdown 2.2.1.

+
+ +
+ + + + + + + diff --git a/docs/reference/logDS.md b/docs/reference/logDS.md new file mode 100644 index 00000000..570e548a --- /dev/null +++ b/docs/reference/logDS.md @@ -0,0 +1,37 @@ +# Computes the logarithm values of the input variable + +This function is similar to R function `log`. + +## Usage + +``` r +logDS(x, base = exp(1)) +``` + +## Arguments + +- x: + + a string character, the name of a numeric or integer vector + +- base: + + a positive number, the base for which logarithms are computed. Default + `exp(1)`. + +## Value + +the object specified by the `newobj` argument of `ds.log` (or default +name `log.newobj`) which is written to the serverside. The output object +is of class numeric. + +## Details + +The function computes the logarithm values of an input numeric or +integer vector. By default natural logarithms are computed. + +## Author + +DataSHIELD Development Team + +Tim Cadman, Genomics Coordination Centre, UMCG, Netherlands diff --git a/docs/reference/lsDS.html b/docs/reference/lsDS.html index 8fdea6b9..b5d1487b 100644 --- a/docs/reference/lsDS.html +++ b/docs/reference/lsDS.html @@ -1,5 +1,5 @@ -lists all objects on a serverside environment — lsDS • dsBaselists all objects on a serverside environment — lsDS • dsBase Skip to contents @@ -9,7 +9,7 @@ dsBase - 6.3.6.9000 + 7.0.0.9000 - - - - - -
-
-
- -

messageDS

- -
messageDS.Rd
-
- -
-

This function allows for error messages arising from the -running of a server-side assign function to be returned to the client-side

-
- -
-

Usage

- 
messageDS(message.object.name)
-
- -
-

Arguments

- - -
message.object.name
-

is a character string, containing the name of the list containing the -message. See the header of the client-side function ds.message for more details.

- -
-
-

Value

-

a list object from each study, containing whatever message has been written by -DataSHIELD into $studysideMessage.

-
-
-

Details

-

Errors arising from aggregate server-side functions can be returned -directly to the client-side. But this is not possible for server-side assign -functions because they are designed specifically to write objects to the -server-side and to return no meaningful information to the client-side. -Otherwise, users may be able to use assign functions to return disclosive -output to the client-side. ds.message calls messageDS which looks -specifically for an object called $serversideMessage in a designated list on -the server-side. Server-side functions from which error messages are to be made -available, are designed to be able to write the designated error message to -the $serversideMessage object into the list that is saved on the server-side -as the primary output of that function. So only valid server-side functions of -DataSHIELD can write a $studysideMessage, and as additional protection against -unexpected ways that someone may try to get round this limitation, a -$studysideMessage is a string that cannot exceed a length of nfilter.string -a default of 80 characters.

-
-
-

Author

-

Burton PR

-
- -
- - -
-

Developed by Paul Burton, Rebecca Wilson, Olly Butters, Patricia Ryser-Welch, Alex Westerberg, Leire Abarrategui, Roberto Villegas-Diaz, Demetris Avraam, Yannick Marcon, Tom Bishop, Amadou Gaye, Xavier Escribà-Montagut, Stuart Wheater.

-
- -
-

Site built with pkgdown 2.2.0.

-
- -
- - - - - - - diff --git a/docs/reference/messageDS.md b/docs/reference/messageDS.md deleted file mode 100644 index d0580a9f..00000000 --- a/docs/reference/messageDS.md +++ /dev/null @@ -1,46 +0,0 @@ -# messageDS - -This function allows for error messages arising from the running of a -server-side assign function to be returned to the client-side - -## Usage - -``` r -messageDS(message.object.name) -``` - -## Arguments - -- message.object.name: - - is a character string, containing the name of the list containing the - message. See the header of the client-side function ds.message for - more details. - -## Value - -a list object from each study, containing whatever message has been -written by DataSHIELD into \$studysideMessage. - -## Details - -Errors arising from aggregate server-side functions can be returned -directly to the client-side. But this is not possible for server-side -assign functions because they are designed specifically to write objects -to the server-side and to return no meaningful information to the -client-side. Otherwise, users may be able to use assign functions to -return disclosive output to the client-side. ds.message calls messageDS -which looks specifically for an object called \$serversideMessage in a -designated list on the server-side. Server-side functions from which -error messages are to be made available, are designed to be able to -write the designated error message to the \$serversideMessage object -into the list that is saved on the server-side as the primary output of -that function. So only valid server-side functions of DataSHIELD can -write a \$studysideMessage, and as additional protection against -unexpected ways that someone may try to get round this limitation, a -\$studysideMessage is a string that cannot exceed a length of -nfilter.string a default of 80 characters. - -## Author - -Burton PR diff --git a/docs/reference/metadataDS.html b/docs/reference/metadataDS.html index 6c2b4036..f819de78 100644 --- a/docs/reference/metadataDS.html +++ b/docs/reference/metadataDS.html @@ -1,5 +1,5 @@ -Returns the metadata, if any, about the specified variable — metadataDS • dsBase +Returns the metadata, if any, about the specified variable — metadataDS • dsBase Skip to contents @@ -7,7 +7,7 @@ dsBase - 6.3.6.9000 + 7.0.0.9000 - - - - - -
-
-
- -

Secure ranking of "V2BR" (vector to be ranked) across all sources

- -
minMaxRandDS.Rd
-
- -
-

Creates a minimum value that is more negative, and less positive -than any real value in V2BR and a maximum value that is more positive and -less negative than any value of V2BR.

-
- -
-

Usage

- 
minMaxRandDS(input.var.name)
-
- -
-

Arguments

- - -
input.var.name
-

a character string specifying the name of V2BR. This -argument is set by the argument with the same name in the clientside function -ds.ranksSecure

- -
-
-

Value

-

the data frame objects containing the global ranks and quantiles. -For more details see the associated document entitled -"secure.global.ranking.docx"

-
-
-

Details

-

Severside aggregate function called by ds.ranksSecure. The minimum -and maximum values it creates are used to replace missing values -(NAs) in V2BR if the argument <NA.manag>e is set to "NA.low" or "NA.hi" -respectively. For more details about the cluster of functions that -collectively enable secure global ranking and estimation of global quantiles -see the associated document entitled "secure.global.ranking.docx". Also -see the header file for ds.ranksSecure

-
-
-

Author

-

Paul Burton 9th November, 2021

-
- -
- - -
-

Developed by Paul Burton, Rebecca Wilson, Olly Butters, Patricia Ryser-Welch, Alex Westerberg, Leire Abarrategui, Roberto Villegas-Diaz, Demetris Avraam, Yannick Marcon, Tom Bishop, Amadou Gaye, Xavier Escribà-Montagut, Stuart Wheater.

-
- -
-

Site built with pkgdown 2.2.0.

-
- -
- - - - - - - diff --git a/docs/reference/minMaxRandDS.md b/docs/reference/minMaxRandDS.md deleted file mode 100644 index d937070b..00000000 --- a/docs/reference/minMaxRandDS.md +++ /dev/null @@ -1,40 +0,0 @@ -# Secure ranking of "V2BR" (vector to be ranked) across all sources - -Creates a minimum value that is more negative, and less positive than -any real value in V2BR and a maximum value that is more positive and -less negative than any value of V2BR. - -## Usage - -``` r -minMaxRandDS(input.var.name) -``` - -## Arguments - -- input.var.name: - - a character string specifying the name of V2BR. This argument is set - by the argument with the same name in the clientside function - ds.ranksSecure - -## Value - -the data frame objects containing the global ranks and quantiles. For -more details see the associated document entitled -"secure.global.ranking.docx" - -## Details - -Severside aggregate function called by ds.ranksSecure. The minimum and -maximum values it creates are used to replace missing values (NAs) in -V2BR if the argument \e is set to "NA.low" or "NA.hi" -respectively. For more details about the cluster of functions that -collectively enable secure global ranking and estimation of global -quantiles see the associated document entitled -"secure.global.ranking.docx". Also see the header file for -ds.ranksSecure - -## Author - -Paul Burton 9th November, 2021 diff --git a/docs/reference/namesDS.html b/docs/reference/namesDS.html index fc6d2abd..843841e8 100644 --- a/docs/reference/namesDS.html +++ b/docs/reference/namesDS.html @@ -1,5 +1,5 @@ -Return the names of a list object — namesDS • dsBase +Return the names of a list object — namesDS • dsBase Skip to contents @@ -7,7 +7,7 @@ dsBase - 6.3.6.9000 + 7.0.0.9000 - - - - - -
-
-
- -

Secure ranking of "V2BR" (vector to be ranked) across all sources

- -
ranksSecureDS1.Rd
-
- -
-

takes key non-disclosive components of the serverside data frame -blackbox.output.df over to the clientside to enable global ranking.

-
- -
-

Usage

- 
ranksSecureDS1()
-
- -
-

Value

-

the non-disclosive elements of blackbox.output.df (see details) -on the serverside as a data frame object (called blackbox.output) -on the clientside. After processing to create the global ranks across all -studies, this is returned to the serverside as the data frame sR4.df using -the clientside function ds.dmtC2S

-
-
-

Details

-

Severside aggregate function called by ds.ranksSecure. The -non-disclosive components of blackbox.output.df that are transmitted to the -clientside are: (1) final values of the "combined real+pseudo data vector" -after all seven rounds of encryption have been completed; (2) a set of -sequential IDs allocated after sorting the "combined real+pseudo data vector" -by value (in ascending order). This allows later re-linkage of values back on -the serverside and confirmation that that linkage is correct. For more -details about the cluster of functions that collectively enable secure global -ranking and estimation of global quantiles see the associated document -entitled "secure.global.ranking.docx". Also see the header file -for ds.ranksSecure

-
-
-

Author

-

Paul Burton 9th November, 2021

-
- -
- - -
-

Developed by Paul Burton, Rebecca Wilson, Olly Butters, Patricia Ryser-Welch, Alex Westerberg, Leire Abarrategui, Roberto Villegas-Diaz, Demetris Avraam, Yannick Marcon, Tom Bishop, Amadou Gaye, Xavier Escribà-Montagut, Stuart Wheater.

-
- -
-

Site built with pkgdown 2.2.0.

-
- -
- - - - - - - diff --git a/docs/reference/ranksSecureDS1.md b/docs/reference/ranksSecureDS1.md deleted file mode 100644 index db7bb40f..00000000 --- a/docs/reference/ranksSecureDS1.md +++ /dev/null @@ -1,37 +0,0 @@ -# Secure ranking of "V2BR" (vector to be ranked) across all sources - -takes key non-disclosive components of the serverside data frame -blackbox.output.df over to the clientside to enable global ranking. - -## Usage - -``` r -ranksSecureDS1() -``` - -## Value - -the non-disclosive elements of blackbox.output.df (see details) on the -serverside as a data frame object (called blackbox.output) on the -clientside. After processing to create the global ranks across all -studies, this is returned to the serverside as the data frame sR4.df -using the clientside function ds.dmtC2S - -## Details - -Severside aggregate function called by ds.ranksSecure. The -non-disclosive components of blackbox.output.df that are transmitted to -the clientside are: (1) final values of the "combined real+pseudo data -vector" after all seven rounds of encryption have been completed; (2) a -set of sequential IDs allocated after sorting the "combined real+pseudo -data vector" by value (in ascending order). This allows later re-linkage -of values back on the serverside and confirmation that that linkage is -correct. For more details about the cluster of functions that -collectively enable secure global ranking and estimation of global -quantiles see the associated document entitled -"secure.global.ranking.docx". Also see the header file for -ds.ranksSecure - -## Author - -Paul Burton 9th November, 2021 diff --git a/docs/reference/ranksSecureDS2.html b/docs/reference/ranksSecureDS2.html deleted file mode 100644 index 6aab7b75..00000000 --- a/docs/reference/ranksSecureDS2.html +++ /dev/null @@ -1,113 +0,0 @@ - -Secure ranking of "V2BR" (vector to be ranked) across all sources — ranksSecureDS2 • dsBase - Skip to contents - - -
-
-
- -

Secure ranking of "V2BR" (vector to be ranked) across all sources

- -
ranksSecureDS2.Rd
-
- -
-

Checks that the data frame produced in creating the initial -global ranks (ranks based on real and pseudo-data after the running of -blackBoxDS)has the correct dimensions and order as the serverside data frames -to which it will now be appended. If either the number of rows or the order -of the rows are inconsistent with the pre-existing data frames on the -serverside an error message is returned and the processing stops. Then -strips out the pseudo-data leaving solely the global ranks based just on -the real data

-
- -
-

Usage

- 
ranksSecureDS2()
-
- -
-

Value

-

creates a new data frame sR5.df on the serverside containing -solely the real data and including key elements needed for next stage of the -ranking process. Most crucially these include "global.rank" and "ID.by.val" -sorted in ascending order of the magnitude of V2BR

-
-
-

Details

-

Severside assign function called by ds.ranksSecure. -It works on the on the output created by serverside function ranksSecureDS1 -and saved on the serverside in data frame sR4.df by ds.dmtC2S. Having -checked QA it strips out all rows corresponding to pseudo-data. The resultant -data frame contains the following vectors: (1) the fully encrypted V2BR -(after application of blackBoxDS);(2) "ID.by.val" the sequential -ID associated with the "combined real+pseudo data vector" sorted by -value (ascending); (3) "studyid", a vector consisting solely of value n in -the nth study; (4) "global.rank" the vector containing global ranks created by -the clientside code in ds.ranksSecure after ranksSecureDS1 is called and up -to the point where ds.dmtC2S sends sR4.df to the serverside. For more -details about the cluster of functions that collectively enable secure global -ranking and estimation of global quantiles see the associated document -entitled "secure.global.ranking.docx". Also see the header file -for ds.ranksSecure

-
-
-

Author

-

Paul Burton 9th November, 2021

-
- -
- - -
-

Developed by Paul Burton, Rebecca Wilson, Olly Butters, Patricia Ryser-Welch, Alex Westerberg, Leire Abarrategui, Roberto Villegas-Diaz, Demetris Avraam, Yannick Marcon, Tom Bishop, Amadou Gaye, Xavier Escribà-Montagut, Stuart Wheater.

-
- -
-

Site built with pkgdown 2.2.0.

-
- -
- - - - - - - diff --git a/docs/reference/ranksSecureDS2.md b/docs/reference/ranksSecureDS2.md deleted file mode 100644 index 78febe60..00000000 --- a/docs/reference/ranksSecureDS2.md +++ /dev/null @@ -1,45 +0,0 @@ -# Secure ranking of "V2BR" (vector to be ranked) across all sources - -Checks that the data frame produced in creating the initial global ranks -(ranks based on real and pseudo-data after the running of blackBoxDS)has -the correct dimensions and order as the serverside data frames to which -it will now be appended. If either the number of rows or the order of -the rows are inconsistent with the pre-existing data frames on the -serverside an error message is returned and the processing stops. Then -strips out the pseudo-data leaving solely the global ranks based just on -the real data - -## Usage - -``` r -ranksSecureDS2() -``` - -## Value - -creates a new data frame sR5.df on the serverside containing solely the -real data and including key elements needed for next stage of the -ranking process. Most crucially these include "global.rank" and -"ID.by.val" sorted in ascending order of the magnitude of V2BR - -## Details - -Severside assign function called by ds.ranksSecure. It works on the on -the output created by serverside function ranksSecureDS1 and saved on -the serverside in data frame sR4.df by ds.dmtC2S. Having checked QA it -strips out all rows corresponding to pseudo-data. The resultant data -frame contains the following vectors: (1) the fully encrypted V2BR -(after application of blackBoxDS);(2) "ID.by.val" the sequential ID -associated with the "combined real+pseudo data vector" sorted by value -(ascending); (3) "studyid", a vector consisting solely of value n in the -nth study; (4) "global.rank" the vector containing global ranks created -by the clientside code in ds.ranksSecure after ranksSecureDS1 is called -and up to the point where ds.dmtC2S sends sR4.df to the serverside. For -more details about the cluster of functions that collectively enable -secure global ranking and estimation of global quantiles see the -associated document entitled "secure.global.ranking.docx". Also see the -header file for ds.ranksSecure - -## Author - -Paul Burton 9th November, 2021 diff --git a/docs/reference/ranksSecureDS3.html b/docs/reference/ranksSecureDS3.html deleted file mode 100644 index 7740a6d8..00000000 --- a/docs/reference/ranksSecureDS3.html +++ /dev/null @@ -1,105 +0,0 @@ - -Secure ranking of "V2BR" (vector to be ranked) across all sources — ranksSecureDS3 • dsBase - Skip to contents - - -
-
-
- -

Secure ranking of "V2BR" (vector to be ranked) across all sources

- -
ranksSecureDS3.Rd
-
- -
-

takes key non-disclosive components of the serverside data frame -blackbox.ranks.df over to the clientside to enable global re-ranking of the -global ranks just applying to the real data (not the pseudo-data).

-
- -
-

Usage

- 
ranksSecureDS3()
-
- -
-

Value

-

the non-disclosive elements of blackbox.output.df (see details) -on the serverside as a data frame object (called sR6.df) -on the clientside. After processing within ds.ranksSecure to create the -global ranks and global quantiles (of real data only) across all studies, -this is returned to the serverside as data frame "global.ranks.quantiles.df" -using the clientside function ds.dmtC2S. To illustrate the difference between -ranks and quantiles, if there are a total of 1000 original real observations -across all studies and one particular observation has the rank 250, it will -have quantile value 0.25 (i.e. 25 -increasing value). Both ranks and quantiles can have ties. For more details -about the cluster of functions that collectively enable secure global ranking -and estimation of global quantiles see the associated document entitled -"secure.global.ranking.docx". Also see the header file for ds.ranksSecure

-
-
-

Details

-

Severside aggregate function called by ds.ranksSecure. The -non-disclosive components of blackbox.ranks.df that are transmitted to the -clientside are: (1) final values of the encrypted global ranks vector -after all seven rounds of encryption have been completed; (2) a set of -sequential IDs allocated to the global ranks vector in each study in their -current order based on increasing value of V2BR. This allows later re-linkage -of values back on the serverside and confirmation that that linkage is -correct. (3) a studyid vector with all values n in the nth study. This -facilitates data management on the serverside during the global ranking -of global ranks. For more details about the cluster of functions that -collectively enable secure global ranking and estimation of global quantiles -see the associated document entitled "secure.global.ranking.docx". Also see -the header file for ds.ranksSecure

-
-
-

Author

-

Paul Burton 9th November, 2021

-
- -
- - -
-

Developed by Paul Burton, Rebecca Wilson, Olly Butters, Patricia Ryser-Welch, Alex Westerberg, Leire Abarrategui, Roberto Villegas-Diaz, Demetris Avraam, Yannick Marcon, Tom Bishop, Amadou Gaye, Xavier Escribà-Montagut, Stuart Wheater.

-
- -
-

Site built with pkgdown 2.2.0.

-
- -
- - - - - - - diff --git a/docs/reference/ranksSecureDS3.md b/docs/reference/ranksSecureDS3.md deleted file mode 100644 index 5602ce29..00000000 --- a/docs/reference/ranksSecureDS3.md +++ /dev/null @@ -1,49 +0,0 @@ -# Secure ranking of "V2BR" (vector to be ranked) across all sources - -takes key non-disclosive components of the serverside data frame -blackbox.ranks.df over to the clientside to enable global re-ranking of -the global ranks just applying to the real data (not the pseudo-data). - -## Usage - -``` r -ranksSecureDS3() -``` - -## Value - -the non-disclosive elements of blackbox.output.df (see details) on the -serverside as a data frame object (called sR6.df) on the clientside. -After processing within ds.ranksSecure to create the global ranks and -global quantiles (of real data only) across all studies, this is -returned to the serverside as data frame "global.ranks.quantiles.df" -using the clientside function ds.dmtC2S. To illustrate the difference -between ranks and quantiles, if there are a total of 1000 original real -observations across all studies and one particular observation has the -rank 250, it will have quantile value 0.25 (i.e. 25 increasing value). -Both ranks and quantiles can have ties. For more details about the -cluster of functions that collectively enable secure global ranking and -estimation of global quantiles see the associated document entitled -"secure.global.ranking.docx". Also see the header file for -ds.ranksSecure - -## Details - -Severside aggregate function called by ds.ranksSecure. The -non-disclosive components of blackbox.ranks.df that are transmitted to -the clientside are: (1) final values of the encrypted global ranks -vector after all seven rounds of encryption have been completed; (2) a -set of sequential IDs allocated to the global ranks vector in each study -in their current order based on increasing value of V2BR. This allows -later re-linkage of values back on the serverside and confirmation that -that linkage is correct. (3) a studyid vector with all values n in the -nth study. This facilitates data management on the serverside during the -global ranking of global ranks. For more details about the cluster of -functions that collectively enable secure global ranking and estimation -of global quantiles see the associated document entitled -"secure.global.ranking.docx". Also see the header file for -ds.ranksSecure - -## Author - -Paul Burton 9th November, 2021 diff --git a/docs/reference/ranksSecureDS4.html b/docs/reference/ranksSecureDS4.html deleted file mode 100644 index 60c03845..00000000 --- a/docs/reference/ranksSecureDS4.html +++ /dev/null @@ -1,121 +0,0 @@ - -Secure ranking of "V2BR" (vector to be ranked) across all sources — ranksSecureDS4 • dsBase - Skip to contents - - -
-
-
- -

Secure ranking of "V2BR" (vector to be ranked) across all sources

- -
ranksSecureDS4.Rd
-
- -
-

Creates a data frame "sR8.df" by cbinding the data frame -"blackBox.ranks.df" with the global ranks and global quantiles vectors in -"global.ranks.quantiles.df". Performs QA on this matrix and orders the -sR8.df data frame according to the argument <ranks.sort.by> in ds.ranksSecure

-
- -
-

Usage

- 
ranksSecureDS4(ranks.sort.by)
-
- -
-

Arguments

- - -
ranks.sort.by
-

a character string taking two possible values. These -are "ID.orig" and "vals.orig". These define the order in which the -output.ranks.df and summary.output.ranks.df data frames are presented. This -argument is set by the argument with the same name in ds.ranksSecure. -Default value is "ID.orig".

- -
-
-

Value

-

Creates the data frame identified by the name given by the argument -(<output.ranks.df>) of the ds.ranksSecure function and writes it to the -serverside. If the argument <output.ranks.df> is NULL or unspecified the -output data frame is called "main.ranks.df". The data frame is ordered -according to the argument <ranks.sort.by> in ds.ranksSecure.

-
-
-

Details

-

Severside assign function called by ds.ranksSecure. -Creates a data frame "sR8.df" by cbinding the data frame "blackBox.ranks.df" -with the global ranks and global quantiles vectors in -"global.ranks.quantiles.df". Checks that all components of sR8.df have the -correct dimensions and are consistent in their ordering. If either the -number of rows or the order of the rows are inconsistent with those in -"blackBox.ranks.df" an error message is returned and the processing stops. -If sR8.df passes all QA tests it is written to the serverside as a data -frame with its name identified by the argument <output.ranks.df> in -ds.ranksSecure. If that argument is NULL or unspecified the data frame -is called "main.ranks.df". The ranksSecureDS4 function also orders the -combined data frame (<output.ranks.df>) in one of two ways: if -the argument <ranks.sort.by> in ds.ranksSecure is set to "ID.orig" the -combined data frame is ordered in the same way as the original V2BR vector; -if the argument <ranks.sort.by> is set to vals.orig" the combined data frame -is ordered by the magnitude of the values of V2BR (ascending). Having -created the data frame (<output.ranks.df>) in this manner it can now be -directly cbinded to either the V2BR vector itself or to a data frame, tibble -or matrix containing V2BR (assuming they are also in the order corresponding -to the argument <ranks.sort.by>) and this combined object can be used as the -basis of analysis based on the global ranks or quantiles including a range -of types of non-parametric analysis.

-
-
-

Author

-

Paul Burton 9th November, 2021

-
- -
- - -
-

Developed by Paul Burton, Rebecca Wilson, Olly Butters, Patricia Ryser-Welch, Alex Westerberg, Leire Abarrategui, Roberto Villegas-Diaz, Demetris Avraam, Yannick Marcon, Tom Bishop, Amadou Gaye, Xavier Escribà-Montagut, Stuart Wheater.

-
- -
-

Site built with pkgdown 2.2.0.

-
- -
- - - - - - - diff --git a/docs/reference/ranksSecureDS4.md b/docs/reference/ranksSecureDS4.md deleted file mode 100644 index 814907c9..00000000 --- a/docs/reference/ranksSecureDS4.md +++ /dev/null @@ -1,62 +0,0 @@ -# Secure ranking of "V2BR" (vector to be ranked) across all sources - -Creates a data frame "sR8.df" by cbinding the data frame -"blackBox.ranks.df" with the global ranks and global quantiles vectors -in "global.ranks.quantiles.df". Performs QA on this matrix and orders -the sR8.df data frame according to the argument \ in -ds.ranksSecure - -## Usage - -``` r -ranksSecureDS4(ranks.sort.by) -``` - -## Arguments - -- ranks.sort.by: - - a character string taking two possible values. These are "ID.orig" and - "vals.orig". These define the order in which the output.ranks.df and - summary.output.ranks.df data frames are presented. This argument is - set by the argument with the same name in ds.ranksSecure. Default - value is "ID.orig". - -## Value - -Creates the data frame identified by the name given by the argument -(\) of the ds.ranksSecure function and writes it to -the serverside. If the argument \ is NULL or -unspecified the output data frame is called "main.ranks.df". The data -frame is ordered according to the argument \ in -ds.ranksSecure. - -## Details - -Severside assign function called by ds.ranksSecure. Creates a data frame -"sR8.df" by cbinding the data frame "blackBox.ranks.df" with the global -ranks and global quantiles vectors in "global.ranks.quantiles.df". -Checks that all components of sR8.df have the correct dimensions and are -consistent in their ordering. If either the number of rows or the order -of the rows are inconsistent with those in "blackBox.ranks.df" an error -message is returned and the processing stops. If sR8.df passes all QA -tests it is written to the serverside as a data frame with its name -identified by the argument \ in ds.ranksSecure. If -that argument is NULL or unspecified the data frame is called -"main.ranks.df". The ranksSecureDS4 function also orders the combined -data frame (\) in one of two ways: if the argument -\ in ds.ranksSecure is set to "ID.orig" the combined -data frame is ordered in the same way as the original V2BR vector; if -the argument \ is set to vals.orig" the combined data -frame is ordered by the magnitude of the values of V2BR (ascending). -Having created the data frame (\) in this manner it -can now be directly cbinded to either the V2BR vector itself or to a -data frame, tibble or matrix containing V2BR (assuming they are also in -the order corresponding to the argument \) and this -combined object can be used as the basis of analysis based on the global -ranks or quantiles including a range of types of non-parametric -analysis. - -## Author - -Paul Burton 9th November, 2021 diff --git a/docs/reference/ranksSecureDS5.html b/docs/reference/ranksSecureDS5.html deleted file mode 100644 index 1bb7537d..00000000 --- a/docs/reference/ranksSecureDS5.html +++ /dev/null @@ -1,121 +0,0 @@ - -Secure ranking of "V2BR" (vector to be ranked) across all sources — ranksSecureDS5 • dsBase - Skip to contents - - -
-
-
- -

Secure ranking of "V2BR" (vector to be ranked) across all sources

- -
ranksSecureDS5.Rd
-
- -
-

Summarises the serverside data frame written by ranksSecureDS4 -which is identified by the name given by the argument (<output.ranks.df>) of -the ds.ranksSecure function to produce a new output data frame containing -only 5 key variables.

-
- -
-

Usage

- 
ranksSecureDS5(output.ranks.df)
-
- -
-

Arguments

- - -
output.ranks.df
-

a character string which specifies an optional name -for the data.frame written to the serverside on each data source that -contains 11 of the key output variables from the ranking procedure pertaining -to that particular data source. This argument is set by the argument with -the same name in ds.ranksSecure.

- -
-
-

Value

-

extracts 5 key vectors from the larger data frame created by -ranksSecureDS4 to produce a summary data frame that is written to the -serverside. It is given a name specified by the argument.

-
-
-

Details

-

Serverside assign function called by clientside function -ds.ranksSecure. Takes the serverside data frame written by ranksSecureDS4 -which is identified by the name given by the argument (<output.ranks.df>) of -the ds.ranksSecure function. This holds 11 vectors including the final -global ranks across all studies and final global quantiles. The data frame -is ordered according to the argument <ranks.sort.by> in ds.ranksSecure. The -ranksSecureDS5 function then extracts 5 key vectors from the larger data -frame to produce a summary data frame that is given a name specified by -the argument (<summary.output.ranks.df>) the ds.ranksSecure function. -This data frame includes the following components: (1) The values of a -sequential ID variable (ID.seq.real.orig) created to lie alongside the -original V2BR vector in the same order as that vector was itself ordered. -These ID values therefore reflect which row in the original data corresponds -to a given row in the output. If the argument <ranks.sort.by> in -ds.ranksSecure is set to "ID.orig" the values of the ID.seq.real.orig vector -in the output data frame simply run sequentially from 1 to N where N is the -number of individuals in the corresponding study. If <ranks.sort.by> is -set to "vals.orig" the values of the ID.seq.real.orig vector will be -determined by the magnitude of the corresponding V2BR value and will -appear to be ordered in a haphazard manner; (2) the original values of V2BR; -(3) the global ranks corresponding to the original values in V2BR, with ties -reflected appropriately; (4) the global quantiles corresponding to the -original values in V2BR, with ties reflected appropriately; (5) a studyid -vector in which all elements take the value n in the nth study.

-
-
-

Author

-

Paul Burton 9th November, 2021

-
- -
- - -
-

Developed by Paul Burton, Rebecca Wilson, Olly Butters, Patricia Ryser-Welch, Alex Westerberg, Leire Abarrategui, Roberto Villegas-Diaz, Demetris Avraam, Yannick Marcon, Tom Bishop, Amadou Gaye, Xavier Escribà-Montagut, Stuart Wheater.

-
- -
-

Site built with pkgdown 2.2.0.

-
- -
- - - - - - - diff --git a/docs/reference/ranksSecureDS5.md b/docs/reference/ranksSecureDS5.md deleted file mode 100644 index 7c4d964b..00000000 --- a/docs/reference/ranksSecureDS5.md +++ /dev/null @@ -1,61 +0,0 @@ -# Secure ranking of "V2BR" (vector to be ranked) across all sources - -Summarises the serverside data frame written by ranksSecureDS4 which is -identified by the name given by the argument (\) of -the ds.ranksSecure function to produce a new output data frame -containing only 5 key variables. - -## Usage - -``` r -ranksSecureDS5(output.ranks.df) -``` - -## Arguments - -- output.ranks.df: - - a character string which specifies an optional name for the data.frame - written to the serverside on each data source that contains 11 of the - key output variables from the ranking procedure pertaining to that - particular data source. This argument is set by the argument with the - same name in ds.ranksSecure. - -## Value - -extracts 5 key vectors from the larger data frame created by -ranksSecureDS4 to produce a summary data frame that is written to the -serverside. It is given a name specified by the argument. - -## Details - -Serverside assign function called by clientside function ds.ranksSecure. -Takes the serverside data frame written by ranksSecureDS4 which is -identified by the name given by the argument (\) of -the ds.ranksSecure function. This holds 11 vectors including the final -global ranks across all studies and final global quantiles. The data -frame is ordered according to the argument \ in -ds.ranksSecure. The ranksSecureDS5 function then extracts 5 key vectors -from the larger data frame to produce a summary data frame that is given -a name specified by the argument (\) the -ds.ranksSecure function. This data frame includes the following -components: (1) The values of a sequential ID variable -(ID.seq.real.orig) created to lie alongside the original V2BR vector in -the same order as that vector was itself ordered. These ID values -therefore reflect which row in the original data corresponds to a given -row in the output. If the argument \ in ds.ranksSecure -is set to "ID.orig" the values of the ID.seq.real.orig vector in the -output data frame simply run sequentially from 1 to N where N is the -number of individuals in the corresponding study. If \ -is set to "vals.orig" the values of the ID.seq.real.orig vector will be -determined by the magnitude of the corresponding V2BR value and will -appear to be ordered in a haphazard manner; (2) the original values of -V2BR; (3) the global ranks corresponding to the original values in V2BR, -with ties reflected appropriately; (4) the global quantiles -corresponding to the original values in V2BR, with ties reflected -appropriately; (5) a studyid vector in which all elements take the value -n in the nth study. - -## Author - -Paul Burton 9th November, 2021 diff --git a/docs/reference/rbindDS.html b/docs/reference/rbindDS.html index e2a48678..b4497ccc 100644 --- a/docs/reference/rbindDS.html +++ b/docs/reference/rbindDS.html @@ -1,5 +1,5 @@ -rbindDS called by ds.rbind — rbindDS • dsBaserbindDS called by ds.rbind — rbindDS • dsBasedsBase - 6.3.6.9000 + 7.0.0.9000 - - - - - -
-
-
- -

Recodes the levels of a categorical variables

- -
recodeLevelsDS.Rd
-
- -
-

The functions uses the input factor and generates a new factor -with new levels.

-
- -
-

Usage

- 
recodeLevelsDS(x = NULL, classes = NULL)
-
- -
-

Arguments

- - -
x
-

a factor vector

- - -
classes
-

a character vector the levels of the newt factor vector

- -
-
-

Value

-

a factor vector with the new levels

-
-
-

Author

-

Gaye, A.

-
- -
- - -
-

Developed by Paul Burton, Rebecca Wilson, Olly Butters, Patricia Ryser-Welch, Alex Westerberg, Leire Abarrategui, Roberto Villegas-Diaz, Demetris Avraam, Yannick Marcon, Tom Bishop, Amadou Gaye, Xavier Escribà-Montagut, Stuart Wheater.

-
- -
-

Site built with pkgdown 2.2.0.

-
- -
- - - - - - - diff --git a/docs/reference/recodeLevelsDS.md b/docs/reference/recodeLevelsDS.md deleted file mode 100644 index f2735ebd..00000000 --- a/docs/reference/recodeLevelsDS.md +++ /dev/null @@ -1,28 +0,0 @@ -# Recodes the levels of a categorical variables - -The functions uses the input factor and generates a new factor with new -levels. - -## Usage - -``` r -recodeLevelsDS(x = NULL, classes = NULL) -``` - -## Arguments - -- x: - - a factor vector - -- classes: - - a character vector the levels of the newt factor vector - -## Value - -a factor vector with the new levels - -## Author - -Gaye, A. diff --git a/docs/reference/recodeValuesDS.html b/docs/reference/recodeValuesDS.html index 540e3a81..42510ae4 100644 --- a/docs/reference/recodeValuesDS.html +++ b/docs/reference/recodeValuesDS.html @@ -1,5 +1,5 @@ -recodeValuesDS an assign function called by ds.recodeValues — recodeValuesDS • dsBaserecodeValuesDS an assign function called by ds.recodeValues — recodeValuesDS • dsBase Skip to contents @@ -9,7 +9,7 @@ dsBase - 6.3.6.9000 + 7.0.0.9000 - - dsBase - 6.3.3 - - - - - - - - - -
-
-
-

Sets the privacy level

- - -
- -
-

This is an internal function that set the number of observation -that are allowed in any table or vector. The function gets the value from the data repository -and if no value was set it uses the default value 5.

-
- -
- 
setFilterDS(x = getOption("datashield.privacyLevel", default = 5))
-
- -
-

Arguments

- - -
x
-

a dummy argument

- -
-
-

Value

-

an integer between 1 and 5

-
-
-

Details

-

The function is called by server side functios

-
-
-

Author

-

Gaye, A.

-
- -
- -
- - -
-

Developed by Paul Burton, Rebecca Wilson, Olly Butters, Patricia Ryser-Welch, Alex Westerberg, Leire Abarrategui, Roberto Villegas-Diaz, Demetris Avraam, Yannick Marcon, Stuart Wheater.

-
- -
-

Site built with pkgdown 2.1.3.

-
- -
- - - - - - - - diff --git a/docs/reference/setSeedDS.html b/docs/reference/setSeedDS.html index 1d0b9286..56396c10 100644 --- a/docs/reference/setSeedDS.html +++ b/docs/reference/setSeedDS.html @@ -1,5 +1,5 @@ -setSeedDs called by ds.setSeed, ds.rNorm, ds.rUnif, ds.rPois and ds.rBinom — setSeedDS • dsBasesetSeedDs called by ds.setSeed, ds.rNorm, ds.rUnif, ds.rPois and ds.rBinom — setSeedDS • dsBase Skip to contents @@ -9,7 +9,7 @@ dsBase - 6.3.6.9000 + 7.0.0.9000 - - - - - -
-
-
- -

Breaks down a dataframe or a factor into its sub-classes

- -
subsetByClassDS.Rd
-
- -
-

The function takes a categorical vector or dataframe as input and generates subset(s) -vectors or dataframes for each category. Subsets are considered invalid if they hold between 1 and -4 observations.

-
- -
-

Usage

- 
subsetByClassDS(data = NULL, variables = NULL)
-
- -
-

Arguments

- - -
data
-

a string character, the name of the dataframe or the factor vector

- - -
variables
-

a vector of string characters, the names of the the variables to subset on.

- -
-
-

Value

-

a list which contains the subsetted datasets

-
-
-

Details

-

If the input data object is a dataframe it is possible to specify the variables -to subset on. If a subset is not 'valid' all its the values are reported as missing (i.e. NA), -the name of the subsets is labelled as '_INVALID'. If no variables are specified to subset on, -the dataframe will be subset on each of its factor variables. -And if none of the columns holds a factor variable a message is issued as output. A message is also -issued as output if the input vector is not of type factor.

-
-
-

Author

-

Gaye, A.

-
- -
- - -
-

Developed by Paul Burton, Rebecca Wilson, Olly Butters, Patricia Ryser-Welch, Alex Westerberg, Leire Abarrategui, Roberto Villegas-Diaz, Demetris Avraam, Yannick Marcon, Tom Bishop, Amadou Gaye, Xavier Escribà-Montagut, Stuart Wheater.

-
- -
-

Site built with pkgdown 2.2.0.

-
- -
- - - - - - - diff --git a/docs/reference/subsetByClassDS.md b/docs/reference/subsetByClassDS.md deleted file mode 100644 index b4ee99c9..00000000 --- a/docs/reference/subsetByClassDS.md +++ /dev/null @@ -1,41 +0,0 @@ -# Breaks down a dataframe or a factor into its sub-classes - -The function takes a categorical vector or dataframe as input and -generates subset(s) vectors or dataframes for each category. Subsets are -considered invalid if they hold between 1 and 4 observations. - -## Usage - -``` r -subsetByClassDS(data = NULL, variables = NULL) -``` - -## Arguments - -- data: - - a string character, the name of the dataframe or the factor vector - -- variables: - - a vector of string characters, the names of the the variables to - subset on. - -## Value - -a list which contains the subsetted datasets - -## Details - -If the input data object is a dataframe it is possible to specify the -variables to subset on. If a subset is not 'valid' all its the values -are reported as missing (i.e. NA), the name of the subsets is labelled -as '\_INVALID'. If no variables are specified to subset on, the -dataframe will be subset on each of its factor variables. And if none of -the columns holds a factor variable a message is issued as output. A -message is also issued as output if the input vector is not of type -factor. - -## Author - -Gaye, A. diff --git a/docs/reference/subsetByClassHelper1.html b/docs/reference/subsetByClassHelper1.html deleted file mode 100644 index 5f03b8e5..00000000 --- a/docs/reference/subsetByClassHelper1.html +++ /dev/null @@ -1,102 +0,0 @@ - -generates subsets vectors from a factor vector — subsetByClassHelper1 • dsBase - - -
-
- - - -
-
-
-

generates subsets vectors from a factor vector

- - -
- -
-

This is an internal function called by the function 'subsetByClassDS'.

-
- -
- 
subsetByClassHelper1(xvect = NULL, xname = NULL, filter = NULL)
-
- -
-

Arguments

- - -
xvect
-

a vector of type factor.

- - -
xname
-

the name of the vector.

- - -
filter
-

the minimum number observation (i.e. rows) that are allowed.

- -
-
-

Value

-

a list which contains the subsets.

-
-
-

Details

-

The function generates subsets if the input of 'subsetByClassDS' is a factor vector.

-
-
-

Author

-

Gaye, A.

-
- -
- -
- - -
-

Developed by Paul Burton, Rebecca Wilson, Olly Butters, Patricia Ryser-Welch, Alex Westerberg, Leire Abarrategui, Roberto Villegas-Diaz, Demetris Avraam, Yannick Marcon, Stuart Wheater.

-
- -
-

Site built with pkgdown 2.1.3.

-
- -
- - - - - - - - diff --git a/docs/reference/subsetByClassHelper2.html b/docs/reference/subsetByClassHelper2.html deleted file mode 100644 index 0363307e..00000000 --- a/docs/reference/subsetByClassHelper2.html +++ /dev/null @@ -1,107 +0,0 @@ - -generates subset tables from a data frame — subsetByClassHelper2 • dsBase - - -
-
- - - -
-
-
-

generates subset tables from a data frame

- - -
- -
-

This is an internal function called by the function 'subsetByClassDS'

-
- -
- 
subsetByClassHelper2(df = NULL, iter = NULL, filter = NULL)
-
- -
-

Arguments

- - -
df
-

a data frame.

- - -
iter
-

the indices of columns to loop trough.

- - -
filter
-

the minimum number of observations (i.e. rows) that are allowed.

- -
-
-

Value

-

a list which contains the subsets, their names and an integer that indicates how many columns were -not factors.

-
-
-

Details

-

The function generates subsets if the input of 'subsetByClassDS' is a data frame -and if the number variables(columns) to subset by are greater than 1; i.e. this -function is called if the user specified more than one variable or no variable to subset by -(if no variables are specified the function 'subsetByClassDS' produces a subset for each category -in each variable).

-
-
-

Author

-

Gaye, A.

-
- -
- -
- - -
-

Developed by Paul Burton, Rebecca Wilson, Olly Butters, Patricia Ryser-Welch, Alex Westerberg, Leire Abarrategui, Roberto Villegas-Diaz, Demetris Avraam, Yannick Marcon, Stuart Wheater.

-
- -
-

Site built with pkgdown 2.1.3.

-
- -
- - - - - - - - diff --git a/docs/reference/subsetByClassHelper3.html b/docs/reference/subsetByClassHelper3.html deleted file mode 100644 index 46aea1ab..00000000 --- a/docs/reference/subsetByClassHelper3.html +++ /dev/null @@ -1,105 +0,0 @@ - -generates subset tables from a data frame — subsetByClassHelper3 • dsBase - - -
-
- - - -
-
-
-

generates subset tables from a data frame

- - -
- -
-

This is an internal function called by the function 'subsetByClassDS'

-
- -
- 
subsetByClassHelper3(df = NULL, indx1 = NULL, filter = NULL)
-
- -
-

Arguments

- - -
df
-

a data frame.

- - -
indx1
-

the column index of the variable specified by the user.

- - -
filter
-

the minimum number of observations (i.e. rows) that are allowed.

- -
-
-

Value

-

a list which contains the subsets, their names and an integer that indicates if -the variable specified by user is a factor.

-
-
-

Details

-

The function generates subsets if the input of 'subsetByClassDS' is a data frame -and if the number of variables (columns) to subset by is 1; i.e. this -function is called if the user specified one variable to subset by.

-
-
-

Author

-

Gaye, A.

-
- -
- -
- - -
-

Developed by Paul Burton, Rebecca Wilson, Olly Butters, Patricia Ryser-Welch, Alex Westerberg, Leire Abarrategui, Roberto Villegas-Diaz, Demetris Avraam, Yannick Marcon, Stuart Wheater.

-
- -
-

Site built with pkgdown 2.1.3.

-
- -
- - - - - - - - diff --git a/docs/reference/subsetDS.html b/docs/reference/subsetDS.html deleted file mode 100644 index 2d7865a8..00000000 --- a/docs/reference/subsetDS.html +++ /dev/null @@ -1,133 +0,0 @@ - -Generates a valid subset of a table or a vector — subsetDS • dsBase - Skip to contents - - -
-
-
- -

Generates a valid subset of a table or a vector

- -
subsetDS.Rd
-
- -
-

The function uses the R classical subsetting with squared brackets '[]' and allows also to -subset using a logical operator and a threshold. The object to subset from must be a vector (factor, numeric -or character) or a table (data.frame or matrix).

-
- -
-

Usage

- 
subsetDS(
-  dt = NULL,
-  complt = NULL,
-  rs = NULL,
-  cs = NULL,
-  lg = NULL,
-  th = NULL,
-  varname = NULL
-)
-
- -
-

Arguments

- - -
dt
-

a string character, the name of the dataframe or the factor vector and the range of the subset.

- - -
complt
-

a boolean that tells if the subset to subset should include only complete cases

- - -
rs
-

a vector of two integers that give the range of rows de extract.

- - -
cs
-

a vector of two integers or one or more characters; the indices of the columns to extract or the names of the columns (i.e. -names of the variables to extract).

- - -
lg
-

a character, the logical parameter to use if the user wishes to subset a vector using a logical -operator. This parameter is ignored if the input data is not a vector.

- - -
th
-

a numeric, the threshold to use in conjunction with the logical parameter. This parameter is ignored -if the input data is not a vector.

- - -
varname
-

a character, if the input data is a table, if this parameter is provided along with the 'logical' and 'threshold' -parameters, a subtable is based the threshold applied to the specified variable. This parameter is however ignored if the parameter -'rows' and/or 'cols' are provided.

- -
-
-

Value

-

a subset of the vector, matrix or dataframe as specified is stored on the server side

-
-
-

Details

-

If the input data is a table: The user specifies the rows and/or columns to include in the subset if the input -object is a table; the columns can be referred to by their names. The name of a vector (i.e. a variable) can also be provided -with a logical operator and a threshold (see example 3). -If the input data is a vector: when the parameters 'rows', 'logical' and 'threshold' are all provided the last two are ignored ( -'rows' has precedence over the other two parameters then). -If the requested subset is not valid (i.e. contains less than the allowed -number of observations), the subset is not generated, rather a table or a vector of missing values is generated to allow -for any subsequent process using the output of the function to proceed after informing the user via a message.

-
-
-

Author

-

Gaye, A.

-
- -
- - -
-

Developed by Paul Burton, Rebecca Wilson, Olly Butters, Patricia Ryser-Welch, Alex Westerberg, Leire Abarrategui, Roberto Villegas-Diaz, Demetris Avraam, Yannick Marcon, Tom Bishop, Amadou Gaye, Xavier Escribà-Montagut, Stuart Wheater.

-
- -
-

Site built with pkgdown 2.2.0.

-
- -
- - - - - - - diff --git a/docs/reference/subsetDS.md b/docs/reference/subsetDS.md deleted file mode 100644 index 11059bdc..00000000 --- a/docs/reference/subsetDS.md +++ /dev/null @@ -1,86 +0,0 @@ -# Generates a valid subset of a table or a vector - -The function uses the R classical subsetting with squared brackets -'\[\]' and allows also to subset using a logical operator and a -threshold. The object to subset from must be a vector (factor, numeric -or character) or a table (data.frame or matrix). - -## Usage - -``` r -subsetDS( - dt = NULL, - complt = NULL, - rs = NULL, - cs = NULL, - lg = NULL, - th = NULL, - varname = NULL -) -``` - -## Arguments - -- dt: - - a string character, the name of the dataframe or the factor vector and - the range of the subset. - -- complt: - - a boolean that tells if the subset to subset should include only - complete cases - -- rs: - - a vector of two integers that give the range of rows de extract. - -- cs: - - a vector of two integers or one or more characters; the indices of the - columns to extract or the names of the columns (i.e. names of the - variables to extract). - -- lg: - - a character, the logical parameter to use if the user wishes to subset - a vector using a logical operator. This parameter is ignored if the - input data is not a vector. - -- th: - - a numeric, the threshold to use in conjunction with the logical - parameter. This parameter is ignored if the input data is not a - vector. - -- varname: - - a character, if the input data is a table, if this parameter is - provided along with the 'logical' and 'threshold' parameters, a - subtable is based the threshold applied to the specified variable. - This parameter is however ignored if the parameter 'rows' and/or - 'cols' are provided. - -## Value - -a subset of the vector, matrix or dataframe as specified is stored on -the server side - -## Details - -If the input data is a table: The user specifies the rows and/or columns -to include in the subset if the input object is a table; the columns can -be referred to by their names. The name of a vector (i.e. a variable) -can also be provided with a logical operator and a threshold (see -example 3). If the input data is a vector: when the parameters 'rows', -'logical' and 'threshold' are all provided the last two are ignored ( -'rows' has precedence over the other two parameters then). If the -requested subset is not valid (i.e. contains less than the allowed -number of observations), the subset is not generated, rather a table or -a vector of missing values is generated to allow for any subsequent -process using the output of the function to proceed after informing the -user via a message. - -## Author - -Gaye, A. diff --git a/docs/reference/table1DDS.html b/docs/reference/table1DDS.html index 9bedc43b..cbdf5cce 100644 --- a/docs/reference/table1DDS.html +++ b/docs/reference/table1DDS.html @@ -1,5 +1,5 @@ -Creates 1-dimensional contingency tables — table1DDS • dsBaseCreates 1-dimensional contingency tables — table1DDS • dsBase Skip to contents @@ -9,7 +9,7 @@ dsBase - 6.3.6.9000 + 7.0.0.9000 - - - - - -
-
-
- -

table2DDS (aggregate function) called by ds.table2D

- -
table2DDS.Rd
-
- -
-

This function generates a 2-dimensional contingency table where potentially disclosive cells -(based on a set threshold) are replaced by a missing value ('NA').

-
- -
-

Usage

- 
table2DDS(xvect, yvect)
-
- -
-

Arguments

- - -
xvect
-

a numerical vector with discrete values - usually a factor.

- - -
yvect
-

a numerical vector with discrete values - usually a factor.

- -
-
-

Value

-

a list which contains two elements: 'table', the 2-dimensional table and 'message' a message which -informs about the validity of the table.

-
-
-

Details

-

It generates 2-dimensional contingency tables where valid (non-disclosive) tables are defined -as those where none of their cells have counts between 1 and the set threshold "nfilter.tab". When the output table -is invalid all cells except the total counts are replaced by missing values. Only the total counts are visible -on the table returned to the client side. A message is also returned with the 2-dimensional table; the message -says "invalid table - invalid counts present" if the table is invalid and 'valid table' otherwise.

-
-
-

Author

-

Amadou Gaye, Paul Burton, Demetris Avraam for DataSHIELD Development Team

-
- -
- - -
-

Developed by Paul Burton, Rebecca Wilson, Olly Butters, Patricia Ryser-Welch, Alex Westerberg, Leire Abarrategui, Roberto Villegas-Diaz, Demetris Avraam, Yannick Marcon, Tom Bishop, Amadou Gaye, Xavier Escribà-Montagut, Stuart Wheater.

-
- -
-

Site built with pkgdown 2.2.0.

-
- -
- - - - - - - diff --git a/docs/reference/table2DDS.md b/docs/reference/table2DDS.md deleted file mode 100644 index 655e2396..00000000 --- a/docs/reference/table2DDS.md +++ /dev/null @@ -1,42 +0,0 @@ -# table2DDS (aggregate function) called by ds.table2D - -This function generates a 2-dimensional contingency table where -potentially disclosive cells (based on a set threshold) are replaced by -a missing value ('NA'). - -## Usage - -``` r -table2DDS(xvect, yvect) -``` - -## Arguments - -- xvect: - - a numerical vector with discrete values - usually a factor. - -- yvect: - - a numerical vector with discrete values - usually a factor. - -## Value - -a list which contains two elements: 'table', the 2-dimensional table and -'message' a message which informs about the validity of the table. - -## Details - -It generates 2-dimensional contingency tables where valid -(non-disclosive) tables are defined as those where none of their cells -have counts between 1 and the set threshold "nfilter.tab". When the -output table is invalid all cells except the total counts are replaced -by missing values. Only the total counts are visible on the table -returned to the client side. A message is also returned with the -2-dimensional table; the message says "invalid table - invalid counts -present" if the table is invalid and 'valid table' otherwise. - -## Author - -Amadou Gaye, Paul Burton, Demetris Avraam for DataSHIELD Development -Team diff --git a/docs/reference/tableDS2.html b/docs/reference/table2DS.html similarity index 76% rename from docs/reference/tableDS2.html rename to docs/reference/table2DS.html index 62a1f762..e29b93a0 100644 --- a/docs/reference/tableDS2.html +++ b/docs/reference/table2DS.html @@ -1,5 +1,5 @@ -tableDS is the second of two serverside aggregate functions called by ds.table — tableDS2 • dsBasetableDS is the second of two serverside aggregate functions called by ds.table — table2DS • dsBase Skip to contents @@ -9,7 +9,7 @@ dsBase - 6.3.6.9000 + 7.0.0.9000