Using Directed Acyclic Graphs to detect limitations of traditional regression in longitudinal studies

Erica Moodie () and D. Stephens

International Journal of Public Health, 2010, vol. 55, issue 6, 703 pages

Abstract: When both time-varying confounding and mediation are present in the data, traditional regression models result in estimates of effect coefficients that are systematically incorrect, or biased. In a companion paper (Moodie and Stephens in Int J Publ Health, 2010b , this issue), we describe a class of models that yield unbiased estimates in a longitudinal setting. Copyright Swiss School of Public Health 2010

Keywords: Confounding; Mediation; Directed Acyclic Graphs; Longitudinal data (search for similar items in EconPapers)
Date: 2010
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DOI: 10.1007/s00038-010-0184-x

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