期刊
EPIDEMIOLOGY
卷 20, 期 4, 页码 488-495出版社
LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/EDE.0b013e3181a819a1
关键词
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资金
- Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development
- National Institutes of Health
- NIH
- NIAID [R03-AI 071763]
- Fonds de Recherche en Sante du Quebec
Overadjustment is defined inconsistently. This term is meant to describe control (eg, by regression adjustment, stratification, or restriction) for a variable that either increases net bias or decreases precision without affecting bias. We define overadjustment bias as control for an intermediate variable (or a descending proxy for an intermediate variable) on a causal path from exposure to outcome. We define unnecessary adjustment as control for a variable that does not affect bias of the causal relation between exposure and outcome but may affect its precision. We use causal diagrams and an empirical example (the effect of maternal smoking on neonatal mortality) to illustrate and clarify the definition of overadjustment bias, and to distinguish overadjustment bias from unnecessary adjustment. Using simulations, we quantify the amount of bias associated with overadjustment. Moreover, we show that this bias is based on a different causal structure from confounding or selection biases. Overadjustment bias is not a finite sample bias, while inefficiencies due to control for unnecessary variables are a function of sample size.
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