Journal Article

When Is Baseline Adjustment Useful in Analyses of Change? An Example with Education and Cognitive Change

M. Maria Glymour, Jennifer Weuve, Lisa F. Berkman, Ichiro Kawachi and James M. Robins

in American Journal of Epidemiology

Published on behalf of Johns Hopkins Bloomberg School of Public Health

Volume 162, issue 3, pages 267-278
Published in print August 2005 | ISSN: 0002-9262
Published online August 2005 | e-ISSN: 1476-6256 | DOI: http://dx.doi.org/10.1093/aje/kwi187
When Is Baseline Adjustment Useful in Analyses of Change? An Example with Education and Cognitive Change

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In research on the determinants of change in health status, a crucial analytic decision is whether to adjust for baseline health status. In this paper, the authors examine the consequences of baseline adjustment, using for illustration the question of the effect of educational attainment on change in cognitive function in old age. With data from the US-based Assets and Health Dynamics Among the Oldest Old survey (n = 5,726; born before 1924), they show that adjustment for baseline cognitive test score substantially inflates regression coefficient estimates for the effect of schooling on change in cognitive test scores compared with models without baseline adjustment. To explain this finding, they consider various plausible assumptions about relations among variables. Each set of assumptions is represented by a causal diagram. The authors apply simple rules for assessing causal diagrams to demonstrate that, in many plausible situations, baseline adjustment induces a spurious statistical association between education and change in cognitive score. More generally, when exposures are associated with baseline health status, this bias can arise if change in health status preceded baseline assessment or if the dependent variable measurement is unreliable or unstable. In some cases, change-score analyses without baseline adjustment provide unbiased causal effect estimates when baseline-adjusted estimates are biased.

Keywords: bias (epidemiology); cognition; educational status; epidemiologic methods; longitudinal studies; models, statistical; neuropsychological tests; regression analysis; DAG, directed acyclic graph; AHEAD, Assets and Health Dynamics Among the Oldest Old

Journal Article.  8253 words.  Illustrated.

Subjects: Public Health and Epidemiology

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