Beyond Analysis of Variance Techniques: Some Applications in Clinical Trials

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Abstract
Clinical trials often have special features that require other methods of analysis besides the usual analysis of variance techniques. For example, data are usually not normally distributed and frequently are in the form of rank data or ordered categorical data. The cumulative chi-squared statistic and its maximal component are proposed as nonparametric tests for analyzing such data. They offer not only robustness Of validity but also that of efficiency. These two statistics are useful generally for modelling and analyzing data in situations where there is an ordering in the parameters. The cumulative chi-squared statistic is applied to the profile analysis of repeated measures that require taking the natural ordering along the time axis into account. The maximal component statistic is applied to a dose finding experiment where a particular multiple comparison procedure is required for ordered parameters corresponding to dose levels. Other problems addressed in the paper include various kinds of multiplicity problems and the proving equivalence of a test drug to the standard which require a quite different approach from the usual significance tests.

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