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

A random intercepts-functional slopes model for flexible assessment of susceptibility in longitudinal designs.
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DOI:
10.1111/j.1541-0420.2010.01461.x
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发表时间:
2011-06
期刊:
影响因子:
1.9
通讯作者:
Coull BA
Coull BA
中科院分区:
数学3区
文献类型:
--
作者:
Coull BA

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In many biomedical investigations, a primary goal is the identification of subjects that 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, and apply the model to data on the effects of particulate matter on coronary blood flow from an animal toxicology study. The general principles introduced here apply more broadly to settings in which interest focuses on the relationship between baseline and change over time.
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