Semi-parametric generalized estimating equations for repeated measurements in cross-over designs
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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.
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