  A model for cross-over designs with repeated measures within each period was
developed. It is obtained using an extension of generalized estimating
equations that includes a parametric component to model treatment effects and a
non-parametric component to model time and carry-over effects; the estimation
approach for the non-parametric component is based on splines. A simulation
study was carried out to explore the model properties. Thus, when there is a
carry-over effect or a functional temporal effect, the proposed model presents
better results than the standard models. Among the theoretical properties, the
solution is found to be analogous to weighted least squares. Therefore, model
diagnostics can be made adapting the results from a multiple regression. The
proposed methodology was implemented in the data sets of the crossover
experiments that motivated the approach of this work: systolic blood pressure
and insulin in rabbits.
