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Abstract:
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This study examined stepwise discriminant analysis (DA) as a post hoc procedure to a significant MANOVA. Monte Carlo simulations were conducted under the assumptions of normality and homogeneity, using different levels of sample size, effect size, a, number of dependent variables, and correlation structure among the dependent variables. High correlations among dependent variables and large numbers of dependent variables led to poor results for power and/or type I error using stepwise DA. However, under certain conditions, stepwise DA performed quite well. The most important factor is keeping the number of dependent variables small, in this study no more than 3. As values for p and sample size increased, type I error became too difficult to control, even for small a, and therefore stepwise DA is not recommended under these conditions.
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