Selection of terms in random coefficient regression models

Francisco M. M. Rocha and Julio M. Singer

Journal of Applied Statistics, 2018, vol. 45, issue 2, 225-242

Abstract: The selection of suitable terms in random coefficient regression models is a challenging problem to practitioners. Although many techniques, ranging from those with a theoretical flavour to those with an exploratory spirit, have been proposed for such purposes, no particular one may be considered as a paradigm. In fact, many authors advocate that they should be used in a complementary way. We consider exploratory methods based on fitting standard regression models to the individual response profiles or to the rows of the sample within-units covariance matrix (for balanced data) that may serve as additional tools in the process of selecting an appropriate model. We evaluate the performance of the proposal via a simulation study and consider applications to two examples in the field of Biostatistics.

Date: 2018
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DOI: 10.1080/02664763.2016.1273884

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