Statistical models for the genetic analysis of longitudinal data.

INTRODUCTION A simple and efficient procedure for the genetic analysis of characters that change as a function of age (or some other independent and continuous variable) is desirable. Three methodologies have been put forward in the literature: random regression, character processes and structured antedependence models. The aim of this paper is to compare the different approaches for the genetic analysis of longitudinal data. We focus on examining the underlying assumptions of the three models, on describing the types of covariance structures (genetic, environmental) accommodated by each method and on evaluating their ability to adequately fit empirical data.

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