Evaluating the Efficacy of Conditional Analysis of Variance Under Non-Normality and Heterogeneity

• In Event: 53.067 - Statistical Research in the Contexts of Parametric Assumption Violations, Simulation, Structural Equation Modeling, and Ordinal or Nominal Data Analyses

Abstract

The analysis of variance (ANOVA) F test is a commonly used method to test the mean equality among two or more populations. A critical assumption of ANOVA is homogeneity of variance (HOV), that is, the compared groups have equal variances. Although it is encouraged to test HOV as part of the regular ANOVA procedure, the efficacy of the initial HOV screening that leads to the choice between the ANOVA F test and robust ANOVA methods (namely, conditional ANOVA) has not been investigated. This simulation study examines the efficacy of conditional ANOVA methods under various research conditions and compares this conditional approach with unconditional ANOVA. Results will provide guidelines for researchers in the selection of an appropriate ANOVA test.

Authors

• Yan Wang, University of South Florida

• Eunsook Kim, University of South Florida

• Diep Thi Nguyen, University of South Florida

• Thanh Vinh Pham, University of South Florida

• Yi-Hsin Chen, University of South Florida

• Zhiyao Yi, Title (Optional)

• Yue Yin, University of South Florida

• Jeffrey D. Kromrey, University of South Florida