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Abstract

The inflation of Type I error rates caused by the testing of multiple null hypotheses in factorial analyses of variance (ANOVAs) is a problem that is often not recognized in the behavioral sciences. Fletcher, Daw, and Young (1989) described the problem and conducted a limited simulation study to investigate the effectiveness of two strategies to correct the problem: use of an overall F test and use of a Bonferroni adjustment. Unfortunately, two limitations in the design of their simulation led these authors to conclusions about the overall F test that do not hold under all conditions. The present study was designed to overcome these limitations and to provide a more complete evaluation of such strategies. Our results indicated that the overall F test is effective only when all effects in the ANOVA are null. In contrast, the Bonferroni adjustment and recent modifications of the procedure control the Type I error rate regardless of the number of true null hypotheses in the ANOVA.

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The Use of an Overall F Test to Control Type I Error Rates in Factorial Analyses of Variance: Limitations and Better Strategies

Abstract

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