Selection of terms in random coefficient regression models

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.

KEYWORDS:

• Covariance matrix
• longitudinal data
• mixed models
• parallel plots
• random coefficient models
• repeated measures

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research was supported by grants from the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq, grant 3304126/2015-2) and Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP, grant 2013/21728-2), Brazil.