A random intercepts-functional slopes model for flexible assessment of susceptibility in longitudinal designs.

ABSTRACT: In many biomedical investigations, a primary goal is the identification of subjects who are susceptible to a given exposure or treatment of interest. We focus on methods for addressing this question in longitudinal studies when interest focuses on relating susceptibility to a subject's baseline or mean outcome level. In this context, we propose a random intercepts-functional slopes model that relaxes the assumption of linear association between random coefficients in existing mixed models and yields an estimate of the functional form of this relationship. We propose a penalized spline formulation for the nonparametric function that represents this relationship, and implement a fully Bayesian approach to model fitting. We investigate the frequentist performance of our method via simulation,

SUBMITTER: Coull BA 

PROVIDER: S-EPMC4446058 | biostudies-literature | 2011 Jun

REPOSITORIES: biostudies-literature