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Hmisc Functions Related to Multivariate Analysis

Function	Purpose
`aregImpute`	Multiple imputation using generalized additive models
`dataRep`	Representativeness of observations in a data set
`find.matches`	Find close matches
`mApply`	Summarize scalars or matrices by cross-classification
`pc1`	Compute and show coefficients (on original scale) first principal component
`rm.boot`	Bootstrap repeated measurements with approximate simultaneous confidence bands for profiles
`summarize`	Summarize scalars or matrices by cross-classification
`summary.formula`	Descriptive statistics, including multiple-number summaries of multiple variables
`transace`	Additive regression and transformation of a matrix of variables
`transcan`	Nonlinear principal components using canonical variates, data reduction, and single imputation
`varclus`	Clustering of variables

Click on a function name to see the function's help file. Note that mApply, summarize, and summary.formula can compute multivariate summary statistics on univariate and multivariate data.

Topic revision: r2 - 14 Dec 2005, FrankHarrell

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