COVARIATE MEASUREMENT ERROR AND THE ESTIMATION OF RANDOM EFFECT PARAMETERS IN A MIXED-MODEL FOR LONGITUDINAL DATA

Citation
Td. Tosteson et al., COVARIATE MEASUREMENT ERROR AND THE ESTIMATION OF RANDOM EFFECT PARAMETERS IN A MIXED-MODEL FOR LONGITUDINAL DATA, Statistics in medicine, 17(17), 1998, pp. 1959-1971
Citations number
16
Categorie Soggetti
Statistic & Probability","Medicine, Research & Experimental","Public, Environmental & Occupation Heath","Statistic & Probability","Medical Informatics
Journal title
ISSN journal
02776715
Volume
17
Issue
17
Year of publication
1998
Pages
1959 - 1971
Database
ISI
SICI code
0277-6715(1998)17:17<1959:CMEATE>2.0.ZU;2-7
Abstract
We explore the effects of measurement error in a time-varying covariat e for a mixed model applied to a longitudinal study of plasma levels a nd dietary intake of beta-carotene. We derive a simple expression for the bias of large sample estimates of the variance of random effects i n a longitudinal model for plasma levels when dietary intake is treate d as a time-varying covariate subject to measurement error. In general , estimates for these variances made without consideration of measurem ent error are biased positively, unlike estimates for the slope coeffi cients which tend to be 'attenuated'. If we can assume that the residu als from a longitudinal fit for the time-varying covariate behave like measurement errors, we can estimate the original parameters without t he need for additional validation or reliability studies. We propose a method to test this assumption and show that the assumption is reason able for the example data. We then use a likelihood-based method of es timation that involves a simple extension of existing methods for fitt ing mixed models. Simulations illustrate the properties of the propose d estimators. (C) 1998 John Wiley & Sons, Ltd.