Confounding in health research.
Consideration of confounding is fundamental to the design, analysis, and interpretation of studies intended to estimate causal effects. Unfortunately, the word confounding has been used synonymously with several other terms, and it has been used to refer to at least four distinct concepts. This paper provides an overview of confounding and related concepts based on a counterfactual model of causation. In this context, which predominates in nonexperimental research, confounding is a source of bias in the estimation of causal effects. Special attention is given to the history of definitions of confounding, the distinction between confounding and confounders, problems in the control of confounding, the relations of confounding to exchangeability and collapsibility, and confounding in randomized trials.
Greenland
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Department of Epidemiology, Los Angeles School of Public Health, University of California, Los Angeles, California 90095-1772, USA. HalM@ucla.edu
Morgenstern
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D015982:Bias; D015984:Causality; D015986:Confounding Factors, Epidemiologic; D004812:Epidemiologic Methods; D006801:Humans; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data; D012107:Research Design