Testing Mean Equality Under Heterogeneity and Nonnormality: An Empirical Comparison of Tests for One-Factor Models

• In Event: Roundtable Session 31
  In Roundtable Session: Alternatives to Parametric Analysis in the Contexts of Regression and Analysis of Variance

Abstract

Analysis of Variance (ANOVA) is a common method to examine the equality of several independent group means. Although the ANOVA F-test is one of the most popular statistical tools to test group mean equivalence, it is sensitive to the violation of the homogeneity of variance assumption. Several alternative tests have been developed in response to this problem of ANOVA F test such as modification of ANOVA F test based on Structured Means Modeling technique. This simulation study examines the performance of fourteen tests in one-factor ANOVA models in terms of their Type I error rate and statistical power under numerous conditions, especially, under the violation of homogeneity of variance assumption.

Authors

• Diep Thi Nguyen, University of South Florida

• Eun Sook Kim, University of South Florida

• Thanh Vinh Pham, University of South Florida

• Yan Wang, University of South Florida

• Jeffrey D. Kromrey, University of South Florida

• Yi-Hsin Chen, University of South Florida