Function reference • dsBaseClient

All functions
`ds.Boole()`	Converts a server-side R object into Boolean indicators
`ds.abs()`	Computes the absolute values of a variable
`ds.asCharacter()`	Converts a server-side R object into a character class
`ds.asDataMatrix()`	Converts a server-side R object into a matrix
`ds.asFactor()`	Converts a server-side numeric vector into a factor
`ds.asFactorSimple()`	Converts a numeric vector into a factor
`ds.asInteger()`	Converts a server-side R object into an integer class
`ds.asList()`	Converts a server-side R object into a list
`ds.asLogical()`	Converts a server-side R object into a logical class
`ds.asMatrix()`	Converts a server-side R object into a matrix
`ds.asNumeric()`	Converts a server-side R object into a numeric class
`ds.assign()`	Assigns an R object to a name in the server-side
`ds.auc()`	Calculates the Area under the curve (AUC)
`ds.boxPlot()`	Draw boxplot
`ds.boxPlotGG()`	Renders boxplot
`ds.boxPlotGG_data_Treatment()`	Take a data frame on the server side an arrange it to pass it to the boxplot function
`ds.boxPlotGG_data_Treatment_numeric()`	Take a vector on the server side an arrange it to pass it to the boxplot function
`ds.boxPlotGG_numeric()`	Draw boxplot with information from a numeric vector
`ds.boxPlotGG_table()`	Draw boxplot with information from a data frame
`ds.bp_standards()`	Calculates Blood pressure z-scores
`ds.c()`	Combines values into a vector or list in the server-side
`ds.cbind()`	Combines R objects by columns in the server-side
`ds.changeRefGroup()`	Changes the reference level of a factor in the server-side
`ds.class()`	Class of the R object in the server-side
`ds.colnames()`	Produces column names of the R object in the server-side
`ds.completeCases()`	Identifies complete cases in server-side R objects
`ds.contourPlot()`	Generates a contour plot
`ds.cor()`	Calculates the correlation of R objects in the server-side
`ds.corTest()`	Tests for correlation between paired samples in the server-side
`ds.cov()`	Calculates the covariance of R objects in the server-side
`ds.dataFrame()`	Generates a data frame object in the server-side
`ds.dataFrameFill()`	Creates missing values columns in the server-side
`ds.dataFrameSort()`	Sorts data frames in the server-side
`ds.dataFrameSubset()`	Sub-sets data frames in the server-side
`ds.densityGrid()`	Generates a density grid in the client-side
`ds.dim()`	Retrieves the dimension of a server-side R object
`ds.dmtC2S()`	Copy a clientside data.frame, matrix or tibble to the serverside
`ds.elspline()`	Basis for a piecewise linear spline with meaningful coefficients
`ds.exists()`	Checks if an object is defined on the server-side
`ds.exp()`	Computes the exponentials in the server-side
`ds.extractQuantiles()`	Secure ranking of a vector across all sources and use of these ranks to estimate global quantiles across all studies
`ds.forestplot()`	Forestplot for SLMA models
`ds.gamlss()`	Generalized Additive Models for Location Scale and Shape
`ds.getWGSR()`	Computes the WHO Growth Reference z-scores of anthropometric data
`ds.glm()`	Fits Generalized Linear Model
`ds.glmPredict()`	Applies predict.glm() to a serverside glm object
`ds.glmSLMA()`	Fit a Generalized Linear Model (GLM) with pooling via Study Level Meta-Analysis (SLMA)
`ds.glmSummary()`	Summarize a glm object on the serverside
`ds.glmerSLMA()`	Fits Generalized Linear Mixed-Effect Models via Study-Level Meta-Analysis
`ds.heatmapPlot()`	Generates a Heat Map plot
`ds.hetcor()`	Heterogeneous Correlation Matrix
`ds.histogram()`	Generates a histogram plot
`ds.igb_standards()`	Converts birth measurements to intergrowth z-scores/centiles
`ds.isNA()`	Checks if a server-side vector is empty
`ds.isValid()`	Checks if a server-side object is valid
`ds.kurtosis()`	Calculates the kurtosis of a numeric variable
`ds.length()`	Gets the length of an object in the server-side
`ds.levels()`	Produces levels attributes of a server-side factor
`ds.lexis()`	Represents follow-up in multiple states on multiple time scales
`ds.list()`	Constructs a list of objects in the server-side
`ds.listClientsideFunctions()`	Lists client-side functions
`ds.listDisclosureSettings()`	Lists disclosure settings
`ds.listServersideFunctions()`	Lists server-side functions
`ds.lmerSLMA()`	Fits Linear Mixed-Effect model via Study-Level Meta-Analysis
`ds.log()`	Computes logarithms in the server-side
`ds.look()`	Performs direct call to a server-side aggregate function
`ds.ls()`	lists all objects on a server-side environment
`ds.lspline()`	Basis for a piecewise linear spline with meaningful coefficients
`ds.make()`	Calculates a new object in the server-side
`ds.matrix()`	Creates a matrix on the server-side
`ds.matrixDet()`	Calculates de determinant of a matrix in the server-side
`ds.matrixDet.report()`	Returns matrix determinant to the client-side
`ds.matrixDiag()`	Calculates matrix diagonals in the server-side
`ds.matrixDimnames()`	Specifies the dimnames of the server-side matrix
`ds.matrixInvert()`	Inverts a server-side square matrix
`ds.matrixMult()`	Calculates tow matrix multiplication in the server-side
`ds.matrixTranspose()`	Transposes a server-side matrix
`ds.mean()`	Computes server-side vector statistical mean
`ds.meanByClass()`	Computes the mean and standard deviation across categories
`ds.meanSdGp()`	Computes the mean and standard deviation across groups defined by one factor
`ds.merge()`	Merges two data frames in the server-side
`ds.message()`	Returns server-side messages to the client-side
`ds.metadata()`	Gets the metadata associated with a variable held on the server
`ds.mice()`	Multivariate Imputation by Chained Equations
`ds.names()`	Return the names of a list object
`ds.ns()`	Generate a Basis Matrix for Natural Cubic Splines
`ds.numNA()`	Gets the number of missing values in a server-side vector
`ds.qlspline()`	Basis for a piecewise linear spline with meaningful coefficients
`ds.quantileMean()`	Computes the quantiles of a server-side variable
`ds.rBinom()`	Generates Binomial distribution in the server-side
`ds.rNorm()`	Generates Normal distribution in the server-side
`ds.rPois()`	Generates Poisson distribution in the server-side
`ds.rUnif()`	Generates Uniform distribution in the server-side
`ds.ranksSecure()`	Secure ranking of a vector across all sources
`ds.rbind()`	Combines R objects by rows in the server-side
`ds.reShape()`	Reshapes server-side grouped data
`ds.recodeLevels()`	Recodes the levels of a server-side factor vector
`ds.recodeValues()`	Recodes server-side variable values
`ds.rep()`	Creates a repetitive sequence in the server-side
`ds.replaceNA()`	Replaces the missing values in a server-side vector
`ds.rm()`	Deletes server-side R objects
`ds.rowColCalc()`	Computes rows and columns sums and means in the server-side
`ds.sample()`	Performs random sampling and permuting of vectors, dataframes and matrices
`ds.scatterPlot()`	Generates non-disclosive scatter plots
`ds.seq()`	Generates a sequence in the server-side
`ds.setSeed()`	Server-side random number generation
`ds.skewness()`	Calculates the skewness of a server-side numeric variable
`ds.sqrt()`	Computes the square root values of a variable
`ds.subset()`	Generates a valid subset of a table or a vector
`ds.subsetByClass()`	Generates valid subset(s) of a data frame or a factor
`ds.summary()`	Generates the summary of a server-side object
`ds.table()`	Generates 1-, 2-, and 3-dimensional contingency tables with option of assigning to serverside only and producing chi-squared statistics
`ds.table1D()`	Generates 1-dimensional contingency tables
`ds.table2D()`	Generates 2-dimensional contingency tables
`ds.tapply()`	Applies a Function Over a Server-Side Ragged Array
`ds.tapply.assign()`	Applies a Function Over a Ragged Array on the server-side
`ds.testObjExists()`	Checks if an R object exists on the server-side
`ds.unList()`	Flattens Server-Side Lists
`ds.unique()`	Perform 'unique' on a variable on the server-side
`ds.var()`	Computes server-side vector variance
`ds.vectorCalc()`	Performs a mathematical operation on two or more vectors

Reference

All functions