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Model Feedback in Bayesian Propensity Score Estimation

Author

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  • Corwin M. Zigler
  • Krista Watts
  • Robert W. Yeh
  • Yun Wang
  • Brent A. Coull
  • Francesca Dominici

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  • Corwin M. Zigler & Krista Watts & Robert W. Yeh & Yun Wang & Brent A. Coull & Francesca Dominici, 2013. "Model Feedback in Bayesian Propensity Score Estimation," Biometrics, The International Biometric Society, vol. 69(1), pages 263-273, March.
    • Handle: RePEc:bla:biomet:v:69:y:2013:i:1:p:263-273
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2012.01830.x
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    References listed on IDEAS

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    1. Lawrence C. McCandless & Sylvia Richardson & Nicky Best, 2012. "Adjustment for Missing Confounders Using External Validation Data and Propensity Scores," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(497), pages 40-51, March.
    2. Chi Wang & Giovanni Parmigiani & Francesca Dominici, 2012. "Bayesian Effect Estimation Accounting for Adjustment Uncertainty," Biometrics, The International Biometric Society, vol. 68(3), pages 661-671, September.
    3. Chi Wang & Giovanni Parmigiani & Francesca Dominici, 2012. "Rejoinder: Bayesian Effect Estimation Accounting for Adjustment Uncertainty," Biometrics, The International Biometric Society, vol. 68(3), pages 680-686, September.
    4. Lawrence C. McCandless, 2012. "Discussion of Adjustment Uncertainty and Propensity Scores," Biometrics, The International Biometric Society, vol. 68(3), pages 678-680, September.
    5. McCandless Lawrence C & Douglas Ian J. & Evans Stephen J. & Smeeth Liam, 2010. "Cutting Feedback in Bayesian Regression Adjustment for the Propensity Score," The International Journal of Biostatistics, De Gruyter, vol. 6(2), pages 1-24, March.
    6. Heejung Bang & James M. Robins, 2005. "Doubly Robust Estimation in Missing Data and Causal Inference Models," Biometrics, The International Biometric Society, vol. 61(4), pages 962-973, December.
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    Cited by:

    1. Olli Saarela & David A. Stephens & Erica E. M. Moodie & Marina B. Klein, 2015. "On Bayesian estimation of marginal structural models," Biometrics, The International Biometric Society, vol. 71(2), pages 279-288, June.
    2. 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.
    3. Susan M. Shortreed & Ashkan Ertefaie, 2017. "Outcome‐adaptive lasso: Variable selection for causal inference," Biometrics, The International Biometric Society, vol. 73(4), pages 1111-1122, December.
    4. Matthew Cefalu & Francesca Dominici & Nils Arvold & Giovanni Parmigiani, 2017. "Model averaged double robust estimation," Biometrics, The International Biometric Society, vol. 73(2), pages 410-421, June.
    5. Antonio R. Linero, 2023. "Prior and posterior checking of implicit causal assumptions," Biometrics, The International Biometric Society, vol. 79(4), pages 3153-3164, December.
    6. Kevin P. Josey & Priyanka deSouza & Xiao Wu & Danielle Braun & Rachel Nethery, 2023. "Estimating a Causal Exposure Response Function with a Continuous Error-Prone Exposure: A Study of Fine Particulate Matter and All-Cause Mortality," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 28(1), pages 20-41, March.
    7. Qi Zhou & Catherine McNeal & Laurel A. Copeland & Justin P. Zachariah & Joon Jin Song, 2020. "Bayesian propensity score analysis for clustered observational data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(2), pages 335-355, June.
    8. James M. Robins & Miguel A. Hernán & Larry Wasserman, 2015. "Discussion of “On Bayesian estimation of marginal structural models”," Biometrics, The International Biometric Society, vol. 71(2), pages 296-299, June.
    9. Daniel Daly‐Grafstein & Paul Gustafson, 2023. "Combining parametric and nonparametric models to estimate treatment effects in observational studies," Biometrics, The International Biometric Society, vol. 79(3), pages 1986-1995, September.
    10. Paul Gustafson, 2015. "Discussion of “On Bayesian Estimation of Marginal Structural Models”," Biometrics, The International Biometric Society, vol. 71(2), pages 291-293, June.
    11. Olli Saarela & David A. Stephens & Erica E. M. Moodie & Marina B. Klein, 2015. "Rejoinder “On Bayesian estimation of marginal structural models”," Biometrics, The International Biometric Society, vol. 71(2), pages 299-301, June.
    12. A. Giffin & B. J. Reich & S. Yang & A. G. Rappold, 2023. "Generalized propensity score approach to causal inference with spatial interference," Biometrics, The International Biometric Society, vol. 79(3), pages 2220-2231, September.
    13. Dandan Xu & Michael J. Daniels & Almut G. Winterstein, 2018. "A Bayesian nonparametric approach to causal inference on quantiles," Biometrics, The International Biometric Society, vol. 74(3), pages 986-996, September.
    14. Corwin Matthew Zigler, 2016. "The Central Role of Bayes’ Theorem for Joint Estimation of Causal Effects and Propensity Scores," The American Statistician, Taylor & Francis Journals, vol. 70(1), pages 47-54, February.
    15. Brian J. Reich & Shu Yang & Yawen Guan & Andrew B. Giffin & Matthew J. Miller & Ana Rappold, 2021. "A Review of Spatial Causal Inference Methods for Environmental and Epidemiological Applications," International Statistical Review, International Statistical Institute, vol. 89(3), pages 605-634, December.
    16. F. Swen Kuh & Grace S. Chiu & Anton H. Westveld, 2019. "Modeling National Latent Socioeconomic Health and Examination of Policy Effects via Causal Inference," Papers 1911.00512, arXiv.org.
    17. Swen Kuh & Grace S. Chiu & Anton H. Westveld, 2020. "Latent Causal Socioeconomic Health Index," Papers 2009.12217, arXiv.org, revised Oct 2023.
    18. Ertefaie Ashkan & Asgharian Masoud & Stephens David A., 2018. "Variable Selection in Causal Inference using a Simultaneous Penalization Method," Journal of Causal Inference, De Gruyter, vol. 6(1), pages 1-16, March.

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