Sisvar: a Guide for its Bootstrap procedures in multiple comparisons

Multiple comparisons procedures.

In biomedical research, a common question posed by investigators is whether or not an outcome of interest differs significantly between multiple independent groups of subjects in the study sample. For example, in a randomized clinical trial focusing on differences in a parameter of cardiovascular health such as systolic blood pressure or heart rate that is measured on a continuum, one might mak...

Bootstrap Methods: A Practitioner's Guide

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Pairwise multiple comparisons: a model comparison approach versus stepwise procedures.

Researchers in the behavioural sciences have been presented with a host of pairwise multiple comparison procedures that attempt to obtain an optimal combination of Type I error control, power, and ease of application. However, these procedures share one important limitation: intransitive decisions. Moreover, they can be characterized as a piecemeal approach to the problem rather than a holistic...

Bootstrap Procedures for Testing Homogeneity Hypotheses

Before pooling data on effect sizes (a generic term for parameters of interest in the context of meta-analysis) from different studies, it is important to test for homogeneity of the effect sizes. A well known test for homogeneity is based on Cochran’s chisquare statistic. Our recent investigation showed that when the effect size of interest is a pairwise correlation, Cochran’s homogeneity test...

I I Simultaneous Test Procedures - Some Theory of Multiple Comparisons