1Department of Epidemiology, Los Angeles School of Public Health, University of California, Los Angeles, California 90095-1772, USA. HalM@ucla.edu
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Understanding confounding is crucial for causal effect estimation in research. This paper clarifies confounding, distinguishing it from related terms and exploring its control and implications in various study designs.
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