NDLI: Model Selection of the Effect of Binary Exposures over the Life Course.

Content Provider	World Health Organization (WHO)-Global Index Medicus
Author	Smith, Andrew D. A. C. Heron, Jon Mishra, Gita Gilthorpe, Mark S. Ben-Shlomo, Yoav Tilling, Kate
Description	Country affiliation: United kingdom Author Affiliation: Smith AD ( From the aSchool of Social and Community Medicine, University of Bristol, Bristol, United Kingdom)
Abstract	Epidemiologists are often interested in examining the effect on a later-life outcome of an exposure measured repeatedly over the life course. When different hypotheses for this effect are proposed by competing theories, it is important to identify those most supported by observed data as a first step toward estimating causal associations. One method is to compare goodness-of-fit of hypothesized models with a saturated model, but it is unclear how to judge the 'best' out of two hypothesized models that both pass criteria for a good fit. We developed a new method using the least absolute shrinkage and selection operator to identify which of a small set of hypothesized models explains most of the observed outcome variation. We analyzed a cohort study with repeated measures of socioeconomic position (exposure) through childhood, early- and mid-adulthood, and body mass index (outcome) measured in mid-adulthood. We confirmed previous findings regarding support or lack of support for the following hypotheses: accumulation (number of times exposed), three critical periods (only exposure in childhood, early- or mid-adulthood), and social mobility (transition from low to high socioeconomic position). Simulations showed that our least absolute shrinkage and selection operator approach identified the most suitable hypothesized model with high probability in moderately sized samples, but with lower probability for hypotheses involving change in exposure or highly correlated exposures. Identifying a single, simple hypothesis that represents the specified knowledge of the life course association allows more precise definition of the causal effect of interest.
File Format	HTM / HTML
ISSN	10443983
e-ISSN	15315487
DOI	10.1097/EDE.0000000000000348
Journal	Epidemiology
Issue Number	5
Volume Number	26
Language	English
Publisher	Lippincott Williams & Wilkins
Publisher Date	2015-09-01
Publisher Place	United States
Access Restriction	Open
Subject Keyword	Discipline Public Health Discipline Epidemiology Causality Epidemiologic Research Design Models, Theoretical Body Mass Index Child, Preschool Cohort Studies Computer Simulation Regression Analysis Socioeconomic Factors Research Support, Non-u.s. Gov't
Content Type	Text
Resource Type	Article
Subject	Epidemiology

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Model Selection of the Effect of Binary Exposures over the Life Course

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