A Structural Approach to Selection Bias
Top Cited Papers
- 1 September 2004
- journal article
- research article
- Published by Wolters Kluwer Health in Epidemiology
- Vol. 15 (5) , 615-625
- https://doi.org/10.1097/01.ede.0000135174.63482.43
Abstract
The term “selection bias” encompasses various biases in epidemiology. We describe examples of selection bias in case-control studies (eg, inappropriate selection of controls) and cohort studies (eg, informative censoring). We argue that the causal structure underlying the bias in each example is essentially the same: conditioning on a common effect of 2 variables, one of which is either exposure or a cause of exposure and the other is either the outcome or a cause of the outcome. This structure is shared by other biases (eg, adjustment for variables affected by prior exposure). A structural classification of bias distinguishes between biases resulting from conditioning on common effects (“selection bias”) and those resulting from the existence of common causes of exposure and outcome (“confounding”). This classification also leads to a unified approach to adjust for selection bias.Keywords
This publication has 18 references indexed in Scilit:
- An overview of relations among causal modelling methodsInternational Journal of Epidemiology, 2002
- Fallibility in estimating direct effectsInternational Journal of Epidemiology, 2002
- Causal Knowledge as a Prerequisite for Confounding Evaluation: An Application to Birth Defects EpidemiologyAmerican Journal of Epidemiology, 2002
- Data, Design, and Background Knowledge in Etiologic InferenceEpidemiology, 2001
- Causation of Bias: The EpiscopeEpidemiology, 2001
- Causal Diagrams for Epidemiologic ResearchEpidemiology, 1999
- Causal diagrams for empirical researchBiometrika, 1995
- Identifiability and Exchangeability for Direct and Indirect EffectsEpidemiology, 1992
- A new approach to causal inference in mortality studies with a sustained exposure period—application to control of the healthy worker survivor effectMathematical Modelling, 1986
- An analysis of detection bias and proposed corrections in the study of estrogens and endometrial cancerJournal of Chronic Diseases, 1981