Repeated measures designs involving nonorthogonal variables are being used with increasing frequency in cognitive psychology. Researchers usually analyze the data from such designs inappropriately, probably because the designs are not discussed in standard textbooks on regression. Two commonly used approaches to analyzing repeated measures designs are considered in this article. It is argued that both approaches use inappropriate error terms for testing the effects of independent variables. A more appropriate analysis is presented, and two alternative computational procedures for the analysis are illustrated.