Bayesian approach for a 2 x 2 crossover design with repeated measures: a simulation study

Abstract

In crossover designs, the subjects receive all treatments, according to the groups of sequences formed. Therefore, if carryover effects are present in the model, inferences about the treatments effects become difficult. Furthermore, repeated measures of the response variable can be taken over time in the same experimental unit; however, these measures may be correlated. In this way, we aimed to analyze a 2 x 2 crossover design with repeated measures within the treatment period, using a Bayesian approach. A simulation study was performed to evaluate the performance. The posterior estimates of the model parameters were obtained under non-informative prior distributions and the normal likelihood function. The model performed well with a sample size of 20 subjects, showing even better results with samples of 100 subjects. With larger samples, exact tests for the differences in carryover effects and time effects were obtained. However, the test of time effect proved to be powerful even with small samples. In turn, considering carryover effects different from zero did not influence the estimates of treatment differences, although biased estimates of the period effect were obtained.