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Simplified Bayesian Sensitivity Analysis for Mismeasured and Unobserved Confounders

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  • P. Gustafson
  • L. C. McCandless
  • A. R. Levy
  • S. Richardson

Abstract

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Suggested Citation

  • P. Gustafson & L. C. McCandless & A. R. Levy & S. Richardson, 2010. "Simplified Bayesian Sensitivity Analysis for Mismeasured and Unobserved Confounders," Biometrics, The International Biometric Society, vol. 66(4), pages 1129-1137, December.
    • Handle: RePEc:bla:biomet:v:66:y:2010:i:4:p:1129-1137
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2009.01377.x
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    References listed on IDEAS

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    1. Sander Greenland, 2005. "Multiple‐bias modelling for analysis of observational data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(2), pages 267-306, March.
    2. Paul Gustafson, 2006. "Sample size implications when biases are modelled rather than ignored," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(4), pages 865-881, October.
    3. Tyler J. VanderWeele, 2008. "Sensitivity Analysis: Distributional Assumptions and Confounding Assumptions," Biometrics, The International Biometric Society, vol. 64(2), pages 645-649, June.
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    Cited by:

    1. Hwanhee Hong & Kara E. Rudolph & Elizabeth A. Stuart, 2017. "Bayesian Approach for Addressing Differential Covariate Measurement Error in Propensity Score Methods," Psychometrika, Springer;The Psychometric Society, vol. 82(4), pages 1078-1096, December.
    2. Qi Zhou & Yoo-Mi Chin & James D. Stamey & Joon Jin Song, 2020. "Bayesian sensitivity analysis to unmeasured confounding for misclassified data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(4), pages 577-596, December.

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