The analysis of small-sample multivariate data with applications in clinical trials

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Abstract
This article discusses statistical methods for the analysis of multivariate data arising in clinical trials involving a small number of subjects randomly assigned to one of several treatment groups. Possible violations of traditional assumptions such as variance homogeneity and normality of errors are often dealt with by carrying out the statistical analysis using strategies such as transforming the data or applying nonparametric procedures. Multivariate nonparametric tests provide a realistic alternative for analyzing such data. We present a permutation procedure for analyzing data arising in randomized experiments.