Semiparametric analyses of cross-over data with repeated measures

A model is proposed to analyze data arising from a cross-over experiment in which measurements on a control and an exposed subject are recorded over time within each crossover period. The model uses locally weighted quadratic regression to control for nuisance temporal trends common to both control and exposed subjects within each period and specifies a first-order autoregressive process to account for dependence among measurements within each longitudinal sequence. We apply the model to a motivating data set in which laboratory animals are exposed to concentrated air particles.