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Simple relations between principal stratification and direct and indirect effects

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  • VanderWeele, Tyler J.

Abstract

The concepts of principal strata direct and indirect effects are compared with and contrasted to definitions of direct and indirect effects which make reference to interventions on intermediate variables. Certain simple relations hold for direct effects but not indirect effects.

Suggested Citation

  • VanderWeele, Tyler J., 2008. "Simple relations between principal stratification and direct and indirect effects," Statistics & Probability Letters, Elsevier, vol. 78(17), pages 2957-2962, December.
    • Handle: RePEc:eee:stapro:v:78:y:2008:i:17:p:2957-2962
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    1. Constantine E. Frangakis & Donald B. Rubin & Ming-Wen An & Ellen MacKenzie, 2007. "Principal Stratification Designs to Estimate Input Data Missing Due to Death," Biometrics, The International Biometric Society, vol. 63(3), pages 641-649, September.
    2. Shepherd, Bryan E. & Gilbert, Peter B. & Lumley, Thomas, 2007. "Sensitivity Analyses Comparing Time-to-Event Outcomes Existing Only in a Subset Selected Postrandomization," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 573-582, June.
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    6. Constantine E. Frangakis & Donald B. Rubin, 2002. "Principal Stratification in Causal Inference," Biometrics, The International Biometric Society, vol. 58(1), pages 21-29, March.
    7. Bryan E. Shepherd & Peter B. Gilbert & Yannis Jemiai & Andrea Rotnitzky, 2006. "Sensitivity Analyses Comparing Outcomes Only Existing in a Subset Selected Post-Randomization, Conditional on Covariates, with Application to HIV Vaccine Trials," Biometrics, The International Biometric Society, vol. 62(2), pages 332-342, June.
    8. Donald B. Rubin, 2005. "Causal Inference Using Potential Outcomes: Design, Modeling, Decisions," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 322-331, March.
    9. Barnard J. & Frangakis C.E. & Hill J.L. & Rubin D.B., 2003. "Principal Stratification Approach to Broken Randomized Experiments: A Case Study of School Choice Vouchers in New York City," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 299-323, January.
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    Cited by:

    1. Huber, Martin & Steinmayr, Andreas, 2017. "A Framework for Separating Individual Treatment Effects From Spillover, Interaction, and General Equilibrium Effects," Rationality and Competition Discussion Paper Series 21, CRC TRR 190 Rationality and Competition.
    2. Laura Forastiere & Patrizia Lattarulo & Marco Mariani & Fabrizia Mealli & Laura Razzolini, 2021. "Exploring Encouragement, Treatment, and Spillover Effects Using Principal Stratification, With Application to a Field Experiment on Teens’ Museum Attendance," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(1), pages 244-258, January.
    3. Mealli Fabrizia & Mattei Alessandra, 2012. "A Refreshing Account of Principal Stratification," The International Journal of Biostatistics, De Gruyter, vol. 8(1), pages 1-19, April.
    4. VanderWeele Tyler J, 2011. "Principal Stratification -- Uses and Limitations," The International Journal of Biostatistics, De Gruyter, vol. 7(1), pages 1-14, July.
    5. Viviana Celli, 2019. "Causal Mediation Analysis in Economics: objectives, assumptions, models," Working Papers 12/19, Sapienza University of Rome, DISS.
    6. Yun Li & Jeremy M.G. Taylor & Michael R. Elliott, 2010. "A Bayesian Approach to Surrogacy Assessment Using Principal Stratification in Clinical Trials," Biometrics, The International Biometric Society, vol. 66(2), pages 523-531, June.
    7. Zhichao Jiang & Shu Yang & Peng Ding, 2022. "Multiply robust estimation of causal effects under principal ignorability," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(4), pages 1423-1445, September.
    8. Pearl Judea, 2011. "Principal Stratification -- a Goal or a Tool?," The International Journal of Biostatistics, De Gruyter, vol. 7(1), pages 1-13, March.
    9. Michela Baccini & Alessandra Mattei & Fabrizia Mealli, 2015. "Bayesian inference for causal mechanisms with application to a randomized study for postoperative pain control," Econometrics Working Papers Archive 2015_06, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    10. Laura Forastiere & Fabrizia Mealli & Tyler J. VanderWeele, 2016. "Identification and Estimation of Causal Mechanisms in Clustered Encouragement Designs: Disentangling Bed Nets Using Bayesian Principal Stratification," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(514), pages 510-525, April.
    11. Michael J. Daniels & Jason A. Roy & Chanmin Kim & Joseph W. Hogan & Michael G. Perri, 2012. "Bayesian Inference for the Causal Effect of Mediation," Biometrics, The International Biometric Society, vol. 68(4), pages 1028-1036, December.
    12. Yi-Ju Wang & Teng Yang & Hye-Ji Kim, 2023. "pH Dynamics in Aquaponic Systems: Implications for Plant and Fish Crop Productivity and Yield," Sustainability, MDPI, vol. 15(9), pages 1-20, April.
    13. Martin Huber & Mark Schelker & Anthony Strittmatter, 2022. "Direct and Indirect Effects based on Changes-in-Changes," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 432-443, January.
    14. Julian Wolfson & Peter Gilbert, 2010. "Statistical Identifiability and the Surrogate Endpoint Problem, with Application to Vaccine Trials," Biometrics, The International Biometric Society, vol. 66(4), pages 1153-1161, December.
    15. Viviana Celli, 2022. "Causal mediation analysis in economics: Objectives, assumptions, models," Journal of Economic Surveys, Wiley Blackwell, vol. 36(1), pages 214-234, February.
    16. Zhiwei Zhang & Richard M. Kotz & Chenguang Wang & Shiling Ruan & Martin Ho, 2013. "A Causal Model for Joint Evaluation of Placebo and Treatment-Specific Effects in Clinical Trials," Biometrics, The International Biometric Society, vol. 69(2), pages 318-327, June.
    17. Eva Deuchert & Martin Huber & Mark Schelker, 2019. "Direct and Indirect Effects Based on Difference-in-Differences With an Application to Political Preferences Following the Vietnam Draft Lottery," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(4), pages 710-720, October.
    18. Chanmin Kim & Lucas R. F. Henneman & Christine Choirat & Corwin M. Zigler, 2020. "Health effects of power plant emissions through ambient air quality," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1677-1703, October.
    19. Adam C. Sales, 2017. "Review," Journal of Educational and Behavioral Statistics, , vol. 42(1), pages 69-84, February.
    20. Tyler J. VanderWeele, 2010. "Direct and Indirect Effects for Neighborhood-Based Clustered and Longitudinal Data," Sociological Methods & Research, , vol. 38(4), pages 515-544, May.

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