Alternatives to traditional analysis of covariance

Traditional analysis of covariance (ANCOVA) assumptions beyond those required for analysis of variance (ANOVA) are described as unnecessary. The problem posed by the most common violation of traditional ANCOVA: heterogeneity of dependent variable on covariate regression coefficients across treatments is considered, as is the relationship between linear modelling and ANCOVA. The amelioration of problems due to covariate‐treatment covariation by heterogeneous regression ANCOVA is described and illustrated in terms of a hypothetical experiment. Subsequently, various parametric alternatives to the traditional ANCOVA are presented in terms of the types of analyses they provide. Finally, the theoretical issue of the relationship between the psychological model and the mathematical model is considered briefly.