ANOVA in GLS transform vs. Welch’s ANOVA under heteroscedasticity

Abstract

Heteroscedastic data arise from a population whose sub-populations have different variabilities from one another. In presence of heteroscedasticity, the LS estimators no longer remain the BLUEs, giving rise to wider acceptance regions and confidence intervals for the model parameters. The most conventional way of removing heteroscedasticity is the generalized least square technique. One can perform one-way ANOVA on this transformed data or use Welch’s ANOVA. This paper compares the efficiencies, i.e., the power of these two methods.