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Calibrating Sensitivity Analyses to Observed Covariates in Observational Studies

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  • Jesse Y. Hsu
  • Dylan S. Small

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  • Jesse Y. Hsu & Dylan S. Small, 2013. "Calibrating Sensitivity Analyses to Observed Covariates in Observational Studies," Biometrics, The International Biometric Society, vol. 69(4), pages 803-811, December.
  • Handle: RePEc:bla:biomet:v:69:y:2013:i:4:p:803-811
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    File URL: http://hdl.handle.net/10.1111/biom.12101
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    References listed on IDEAS

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    1. Guildo W. Imbens, 2003. "Sensitivity to Exogeneity Assumptions in Program Evaluation," American Economic Review, American Economic Association, vol. 93(2), pages 126-132, May.
    2. Paul R. Rosenbaum, 1986. "Dropping out of High School in the United States: An Observational Study," Journal of Educational and Behavioral Statistics, , vol. 11(3), pages 207-224, September.
    3. Sue M. Marcus, 1997. "Using Omitted Variable Bias to Assess Uncertainty in the Estimation of an AIDS Education Treatment Effect," Journal of Educational and Behavioral Statistics, , vol. 22(2), pages 193-201, June.
    4. Wei Pan & Kenneth A. Frank, 2003. "A Probability Index of the Robustness of a Causal Inference," Journal of Educational and Behavioral Statistics, , vol. 28(4), pages 315-337, December.
    5. Joseph L. Gastwirth & Abba M. Krieger & Paul R. Rosenbaum, 2000. "Asymptotic separability in sensitivity analysis," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(3), pages 545-555.
    6. Small, Dylan S., 2007. "Sensitivity Analysis for Instrumental Variables Regression With Overidentifying Restrictions," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1049-1058, September.
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    Citations

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    Cited by:

    1. Paul R. Rosenbaum, 2015. "Some Counterclaims Undermine Themselves in Observational Studies," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1389-1398, December.
    2. Byeong Yeob Choi & Jason P. Fine & Roman Fernandez & M. Alan Brookhart, 2022. "Alternative sensitivity analyses for regression estimates of treatment effects to unobserved confounding in binary and survival data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(3), pages 637-659, September.
    3. Giovanni Nattino & Bo Lu, 2018. "Model assisted sensitivity analyses for hidden bias with binary outcomes," Biometrics, The International Biometric Society, vol. 74(4), pages 1141-1149, December.
    4. Bo Zhang & Dylan S. Small, 2020. "A calibrated sensitivity analysis for matched observational studies with application to the effect of second‐hand smoke exposure on blood lead levels in children," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(5), pages 1285-1305, November.
    5. Bo Zhang & Eric J. Tchetgen Tchetgen, 2022. "A semi‐parametric approach to model‐based sensitivity analysis in observational studies," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(S2), pages 668-691, December.
    6. Raiden B. Hasegawa & Sameer K. Deshpande & Dylan S. Small & Paul R. Rosenbaum, 2020. "Causal Inference With Two Versions of Treatment," Journal of Educational and Behavioral Statistics, , vol. 45(4), pages 426-445, August.
    7. Hao Chen & Dylan S. Small, 2022. "New multivariate tests for assessing covariate balance in matched observational studies," Biometrics, The International Biometric Society, vol. 78(1), pages 202-213, March.
    8. Xuran Wang & Yang Jiang & Nancy R. Zhang & Dylan S. Small, 2018. "Sensitivity analysis and power for instrumental variable studies," Biometrics, The International Biometric Society, vol. 74(4), pages 1150-1160, December.
    9. Nathan Kallus & Angela Zhou, 2021. "Minimax-Optimal Policy Learning Under Unobserved Confounding," Management Science, INFORMS, vol. 67(5), pages 2870-2890, May.
    10. Paul R. Rosenbaum, 2015. "Bahadur Efficiency of Sensitivity Analyses in Observational Studies," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 205-217, March.

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