Adjusting for Unequal Variances When Comparing Means in One-Way and Two-Way Fixed Effects ANOVA Models
- 1 September 1989
- journal article
- Published by American Educational Research Association (AERA) in Journal of Educational Statistics
- Vol. 14 (3) , 269-278
- https://doi.org/10.3102/10769986014003269
Abstract
Numerous papers have shown that the conventional F test is not robust to unequal variances in the one-way fixed effects ANOVA model, and several methods have been proposed for dealing with this problem. Here I describe and compare two methods for handling unequal variances in the two-way fixed effects ANOVA model. One is based on an improved Wilcox (1988) method for the one-way model, which forms the basis for considering this method in the two-way ANOVA model. The other is an extension of James’s (1951) second order method.Keywords
This publication has 14 references indexed in Scilit:
- The Fisher‐Pitman permutation test: A non‐robust alternative to the normal theory F test when variances are heterogeneousBritish Journal of Mathematical and Statistical Psychology, 1987
- Comparison of ANOVA alternatives under variance heterogeneity and specific noncentrality structures.Psychological Bulletin, 1986
- A comparison between the U and V tests in the Behrens-Fisher problemBiometrika, 1983
- Testing the equality of several means when the population variances are unequalCommunications in Statistics - Simulation and Computation, 1981
- Exact Analysis of Variance with Unequal Variances: Test Procedures and TablesTechnometrics, 1978
- Is the ANOVA F-Test Robust to Variance Heterogeneity When Sample Sizes are Equal?: An Investigation via a Coefficient of VariationAmerican Educational Research Journal, 1977
- The Small Sample Behavior of Some Statistics Which Test the Equality of Several MeansTechnometrics, 1974
- ON THE COMPARISON OF SEVERAL MEAN VALUES: AN ALTERNATIVE APPROACHBiometrika, 1951
- THE COMPARISON OF SEVERAL GROUPS OF OBSERVATIONS WHEN THE RATIOS OF THE POPULATION VARIANCES ARE UNKNOWNBiometrika, 1951
- A Two-Sample Test for a Linear Hypothesis Whose Power is Independent of the VarianceThe Annals of Mathematical Statistics, 1945