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Selection Bias in Epidemiologic Studies

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Modern Methods for Epidemiology

Abstract

Bias is inherent in epidemiology, and researchers go to great lengths to avoid introducing bias into their studies. However, some bias is inevitable, and bias due to selection is particularly common. We discuss ways to identify bias and how authors have approached removing or adjusting for bias using statistical methods.

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References

  • Breslow, N. E., & Day, N. E. (1980). Statistical methods in cancer research. Vol 1. The analysis of case-control studies. IARC, Lyon.

    Google Scholar 

  • Cleveland, W. S., & Devlin, S. J. (1988). Locally weighted regression: An approach to regression analysis by local fitting. Journal of the American Statistical Association, 83, 596–610.

    Article  Google Scholar 

  • Galea, S., & Tracy, M. (2007). Participation rates in epidemiologic studies. Annals of Epidemiology, 17(9), 643–653. available from: ISI:000249293100001.

    Article  PubMed  Google Scholar 

  • Geneletti, S., Richardson, S., & Best, N. (2009). Adjusting for selection bias in retrospective, case-control studies. Biostatistics, 10(1), 17–31. available from: PM:18482997.

    Article  PubMed  Google Scholar 

  • Greenland, S., & Brumback, B. (2002). An overview of relations among causal modelling methods. International Journal of Epidemiology, 31(5), 1030–1037. available from: PM:12435780.

    Article  PubMed  Google Scholar 

  • Greenland, S., Pearl, J., & Robins, J. M. (1999). Causal diagrams for epidemiologic research. Epidemiology, 10(1), 37–48. available from: PM:9888278.

    Article  PubMed  CAS  Google Scholar 

  • Gunby, J. A., Darby, S. C., Miles, J. C. H., Green, B. M. R., & Cox, D. R. (1993). Factors affecting indoor radon concentrations in the United-Kingdom. Health Physics, 64(1), 2–12. available from: ISI:A1993KD26400002.

    Article  PubMed  CAS  Google Scholar 

  • Henderson, M., & Page, L. (2007). Appraising the evidence: What is selection bias? Evidence-Based Mental Health, 10(3), 67–68. available from: PM:17652553.

    Article  PubMed  Google Scholar 

  • Hernan, M. A., Hernandez-Diaz, S., & Robins, J. M. (2004). A structural approach to selection bias. Epidemiology, 15(5), 615–625. available from: PM:15308962.

    Article  PubMed  Google Scholar 

  • Law, G. R., Smith, A. G., & Roman, E. (2002). The importance of full participation: Lessons from a national case-control study. British Journal of Cancer, 86(3), 350–355. available from: PM:11875698.

    Article  PubMed  CAS  Google Scholar 

  • Law, G. R., Parslow, R. C., & Roman, E. (2003). Childhood cancer and population mixing. American Journal of Epidemiology, 158(4), 328–336. available from: PM:12915498.

    Article  PubMed  Google Scholar 

  • McNamee, R. (2003). Confounding and confounders. Occupational and Environmental Medicine, 60(3), 227–234. available from: PM:12598677.

    Article  PubMed  CAS  Google Scholar 

  • Pearl, J. (2000). Causality: Models, reasoning and inference. New York: Cambridge University Press.

    Google Scholar 

  • Pfeffermann, D. (1996). The use of sampling weights for survey data analysis. Statistical Methods in Medical Research, 5(3), 239–261. available from: PM:8931195.

    Article  PubMed  CAS  Google Scholar 

  • Pfeffermann, D., & Sverchkov, M. Y. U. (2003). Fitting generalised linear models under informative sampling. In R. L. Chambers & C. J. Skinner (Eds.), Analysis of survey data (pp. 175–195). Chichester: Wiley.

    Chapter  Google Scholar 

  • R Development Core Team. (2004). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing.

    Google Scholar 

  • Rubin, D. B. (1976). Inference and missing data. Biometrika, 63(3), 581–590. available from: ISI:A1976CP66700021.

    Article  Google Scholar 

  • Samuelsen, S. O., Anestad, H., & Skrondal, A. (2007). Stratified case-cohort analysis of general cohort sampling designs. Scandinavian Journal of Statistics, 34(1), 103–119. available from: ISI:000244852300008.

    Article  Google Scholar 

  • Schlesselman, J. J. (1982). Case-control studies: Design, conduct, analysis. Oxford: Oxford University Press.

    Google Scholar 

  • Smith, A. G., Fear, N. T., Law, G. R., & Roman, E. (2004). Representativeness of samples from general practice lists in epidemiological studies: Case-control study. BMJ, 328(7445), 932. available from: PM:14990513.

    Article  PubMed  CAS  Google Scholar 

  • The UK Childhood Cancer Study Investigators. (2000). The United Kingdom Childhood Cancer Study: Objectives, materials and methods. UK Childhood Cancer Study Investigators. British Journal of Cancer, 82(5), 1073–1102. available from: PM:10737392.

    Article  Google Scholar 

  • The UK Childhood Cancer Study Investigators. (2002). The United Kingdom Childhood Cancer Study of exposure to domestic sources of ionising radiation: 1: Radon gas. British Journal of Cancer, 86(11), 1721–1726. available from: PM:12087456.

    Article  Google Scholar 

  • Tu, Y.-K., West, R. W., Ellison, G. D. H., & Gilthorpe, M. S. (2004). Why evidence for the fetal origins of adult disease can be statistical artifact: The reversal paradox examined for hypertension. American Journal of Epidemiology, 161(1), 27–32.

    Article  Google Scholar 

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Correspondence to Graham R. Law .

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Law, G.R., Baxter, P.D., Gilthorpe, M.S. (2012). Selection Bias in Epidemiologic Studies. In: Tu, YK., Greenwood, D. (eds) Modern Methods for Epidemiology. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-3024-3_4

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