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The Journals of Gerontology Series A: Biological Sciences and Medical Sciences Advance Access originally published online on February 5, 2009
The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 2009 64A(2):215-222; doi:10.1093/gerona/gln024
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Published by Oxford University Press on behalf of The Gerontological Society of America 2009.

Model Choice Can Obscure Results in Longitudinal Studies

Christopher H. Morrell1,2, Larry J. Brant1 and Luigi Ferrucci3

1 Gerontology Research Center, National Institute on Aging, Baltimore, Maryland
2 Mathematical Sciences Department, Loyola College in Maryland, Baltimore
3 Clinical Research Branch, National Institute on Aging, Harbor Hospital, Baltimore, Maryland

Address correspondence to Larry J. Brant, PhD, Gerontology Research Center, National Institute on Aging, 5600 Nathan Shock Drive, Baltimore, MD 21224. Email: larry_brant{at}nih.gov


  Abstract

Background: This article examines how different parameterizations of age and time in modeling observational longitudinal data can affect results.

Methods: When individuals of different ages at study entry are considered, it becomes necessary to distinguish between longitudinal and cross-sectional differences to overcome possible selection biases.

Results: Various models were fitted using data from longitudinal studies with participants with different ages and different follow-up lengths. Decomposing age into two components—age at entry into the study (first age) and the longitudinal follow-up (time) compared with considering age alone—leads to different conclusions.

Conclusions: In general, models using both first age and time terms performed better, and these terms are usually necessary to correctly analyze longitudinal data.

Keywords Mixed-effects models; Multilevel modeling; Observational study; Recruitment bias; Regression

Received: March 5, 2008; Accepted: June 26, 2008

Decision Editor: Darryl Wieland, PhD, MPH


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