A correlation structure for the analysis of Gaussian and non-Gaussian responses in crossover experimental designs with repeated measures
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Springer Nature
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In this paper, we propose a family of correlation structures for crossover designs with repeated measures for both, Gaussian and non-Gaussian responses using generalized estimating equations (GEE). The structure considers two matrices: one that models between-period correlation and another one that models within-period correlation. The overall correlation matrix, which is used to build the GEE, corresponds to the Kronecker between these matrices. A procedure to estimate the parameters of the correlation matrix is proposed, its statistical properties are studied and a comparison with standard models using a single correlation matrix is carried out. A simulation study showed a superior performance of the proposed structure in terms of the quasi-likelihood criterion, efficiency, and the capacity to explain complex correlation phenomena patterns in longitudinal data from crossover designs.
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Investigación agropecuaria - A50, Datos, Matriz, Correlación genética, Cruzamiento, Transversal, http://aims.fao.org/aos/agrovoc/c_49816, http://aims.fao.org/aos/agrovoc/c_d585d991, http://aims.fao.org/aos/agrovoc/c_29796, http://aims.fao.org/aos/agrovoc/c_1976