Type I Error Rates and Power of Multiple Hypothesis Testing Procedures in Factorial ANOVA
Year: 2013
Type: article
Abstract: There are numerous General Linear Model (GLM) statistical designs that may require multiple hypothesis testing (MHT) procedures that control the Type I error inflation that occurs with multiple tests. This study investigated familywise error rates (FWER) and statistical power rates of several alpha-adjustment MHT procedures in factorial ANOVA, but results apply broadly to GLM procedures. Of four MHT procedures investigated, the Hochberg procedure performed most efficiently in terms of Type I error and power, slightly better than Holm. The Holm procedure, however, may be the better choice because of less restrictive assumptions. FWER concerns were raised with the Benjamini-Hochberg procedure.
Source: General Linear Model Journal
Authors: An, Qian, Xu, Deyu, Brooks, Gordon P.
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W2182137025