The purpose of this chapter is to describe a simple method for emulating repeated-measure ANOVA results using a hierarchical multiple-regression technique. Although this approach is fully described by Cohen and Coehn (1983, chapter 11), it is apparently not known by most behavioral researchers employing repeated measures in complex covariate or quasi-experimental studies. It is especially useful in studies involving two or more IVs that are naturally correlated or correlated due to unequal and disproportionate sample sizes among study groups. Although such conditions violate a basic assumption of the repeated-measures ANOVA, use of a hierarchical regression analysis can emulate an ANOVA and can correctly partition the variance among correlated IVs into shared and unshared portions. This chapter will proceed with a review of the basic features of a simple factorial repeated-measure ANOVA, then show how multiple regression can be used to make the same calculations, and finally suggest how the repeated-measure regression approach might be used to analyze a complex, quasi-experimental study.