IDEAS home Printed from https://ideas.repec.org/a/bpj/causin/v1y2013i1p1-20n1.html

Causal inference under multiple versions of treatment

Author

Listed:
  • VanderWeele Tyler J.

    (Departments of Epidemiology and Biostatistics, Harvard School of Public Health, Massachusetts, United States)

  • Hernan Miguel A.

    (Departments of Epidemiology and Biostatistics, Harvard School of Public Health, Massachusetts, United States)

Abstract

In this article, we discuss causal inference when there are multiple versions of treatment. The potential outcomes framework, as articulated by Rubin, makes an assumption of no multiple versions of treatment, and here we discuss an extension of this potential outcomes framework to accommodate causal inference under violations of this assumption. A variety of examples are discussed in which the assumption may be violated. Identification results are provided for the overall treatment effect and the effect of treatment on the treated when multiple versions of treatment are present and also for the causal effect comparing a version of one treatment to some other version of the same or a different treatment. Further identification and interpretative results are given for cases in which the version precedes the treatment as when an underlying treatment variable is coarsened or dichotomized to create a new treatment variable for which there are effectively “multiple versions”. Results are also given for effects defined by setting the version of treatment to a prespecified distribution. Some of the identification results bear resemblance to identification results in the literature on direct and indirect effects. We describe some settings in which ignoring multiple versions of treatment, even when present, will not lead to incorrect inferences.

Suggested Citation

  • VanderWeele Tyler J. & Hernan Miguel A., 2013. "Causal inference under multiple versions of treatment," Journal of Causal Inference, De Gruyter, vol. 1(1), pages 1-20, June.
    • Handle: RePEc:bpj:causin:v:1:y:2013:i:1:p:1-20:n:1
    DOI: 10.1515/jci-2012-0002
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/jci-2012-0002
    Download Restriction: no
    File URL: https://libkey.io/10.1515/jci-2012-0002?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Sobel, Michael E., 2006. "What Do Randomized Studies of Housing Mobility Demonstrate?: Causal Inference in the Face of Interference," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1398-1407, December.
    2. Halloran M. Elizabeth & Hudgens Michael G., 2012. "Causal Inference for Vaccine Effects on Infectiousness," The International Journal of Biostatistics, De Gruyter, vol. 8(2), pages 1-40, January.
    3. Jin, Hui & Rubin, Donald B., 2008. "Principal Stratification for Causal Inference With Extended Partial Compliance," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 101-111, March.
    4. Hudgens, Michael G. & Halloran, M. Elizabeth, 2008. "Toward Causal Inference With Interference," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 832-842, June.
    5. Hong, Guanglei & Raudenbush, Stephen W., 2006. "Evaluating Kindergarten Retention Policy: A Case Study of Causal Inference for Multilevel Observational Data," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 901-910, September.
    6. VanderWeele, Tyler J. & Tchetgen Tchetgen, Eric J., 2011. "Effect partitioning under interference in two-stage randomized vaccine trials," Statistics & Probability Letters, Elsevier, vol. 81(7), pages 861-869, July.
    7. Rosenbaum, Paul R., 2007. "Interference Between Units in Randomized Experiments," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 191-200, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Emaad Manzoor & Nikhil Malik, 2023. "Designing Effective Music Excerpts," Papers 2309.14475, arXiv.org.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chiba, Yasutaka, 2012. "A note on bounds for the causal infectiousness effect in vaccine trials," Statistics & Probability Letters, Elsevier, vol. 82(7), pages 1422-1429.
    2. Kosuke Imai & Zhichao Jiang, 2020. "Identification and sensitivity analysis of contagion effects in randomized placebo‐controlled trials," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1637-1657, October.
    3. Arpino, Bruno & Mattei, Alessandra, 2013. "Assessing the Impact of Financial Aids to Firms: Causal Inference in the presence of Interference," MPRA Paper 51795, University Library of Munich, Germany.
    4. Lopez-Rivas, Jose D., 2024. "Spreading the word! Effects of a randomized normative informational campaign on residential water conservation," Resource and Energy Economics, Elsevier, vol. 79.
    5. Shaina J. Alexandria & Michael G. Hudgens & Allison E. Aiello, 2023. "Assessing intervention effects in a randomized trial within a social network," Biometrics, The International Biometric Society, vol. 79(2), pages 1409-1419, June.
    6. C. Tort`u & I. Crimaldi & F. Mealli & L. Forastiere, 2020. "Modelling Network Interference with Multi-valued Treatments: the Causal Effect of Immigration Policy on Crime Rates," Papers 2003.10525, arXiv.org, revised Jun 2020.
    7. Rigdon, Joseph & Hudgens, Michael G., 2015. "Exact confidence intervals in the presence of interference," Statistics & Probability Letters, Elsevier, vol. 105(C), pages 130-135.
    8. repec:hal:journl:hal-04549691 is not listed on IDEAS
    9. VanderWeele, Tyler J. & Tchetgen Tchetgen, Eric J., 2011. "Effect partitioning under interference in two-stage randomized vaccine trials," Statistics & Probability Letters, Elsevier, vol. 81(7), pages 861-869, July.
    10. Cai Xiaoxuan & Loh Wen Wei & Crawford Forrest W., 2021. "Identification of causal intervention effects under contagion," Journal of Causal Inference, De Gruyter, vol. 9(1), pages 9-38, January.
    11. Giovanni Cerulli, 2014. "ntreatreg: a Stata module for estimation of treatment effects in the presence of neighborhood interactions," United Kingdom Stata Users' Group Meetings 2014 15, Stata Users Group.
    12. 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.
    13. Sourafel Girma & Yundan Gong & Holger Görg & Sandra Lancheros, 2016. "Estimating direct and indirect effects of foreign direct investment on firm productivity in the presence of interactions between firms," World Scientific Book Chapters, in: MULTINATIONAL ENTERPRISES AND HOST COUNTRY DEVELOPMENT, chapter 12, pages 227-239, World Scientific Publishing Co. Pte. Ltd..
    14. Sujatro Chakladar & Samuel Rosin & Michael G. Hudgens & M. Elizabeth Halloran & John D. Clemens & Mohammad Ali & Michael E. Emch, 2022. "Inverse probability weighted estimators of vaccine effects accommodating partial interference and censoring," Biometrics, The International Biometric Society, vol. 78(2), pages 777-788, June.
    15. Giovanni Cerulli, 2014. "Identification and Estimation of Treatment Effects in the Presence of Neighbourhood Interactions," CERIS Working Paper 201404, CNR-IRCrES Research Institute on Sustainable Economic Growth - Torino (TO) ITALY - former Institute for Economic Research on Firms and Growth - Moncalieri (TO) ITALY.
    16. Mäkinen, Taneli & Li, Fan & Mercatanti, Andrea & Silvestrini, Andrea, 2022. "Causal analysis of central bank holdings of corporate bonds under interference," Economic Modelling, Elsevier, vol. 113(C).
    17. Denis Fougère & Nicolas Jacquemet, 2020. "Policy Evaluation Using Causal Inference Methods," Sciences Po Economics Publications (main) hal-03455978, HAL.
    18. Giulio Grossi & Marco Mariani & Alessandra Mattei & Patrizia Lattarulo & Ozge Oner, 2020. "Direct and spillover effects of a new tramway line on the commercial vitality of peripheral streets. A synthetic-control approach," Papers 2004.05027, arXiv.org, revised Nov 2023.
    19. Clarke, Damian, 2017. "Estimating Difference-in-Differences in the Presence of Spillovers," MPRA Paper 81604, University Library of Munich, Germany.
    20. Xiang, Xunyong & Liu, Ruier & Luo, Wenjie, 2024. "Pollution haven or pollution halo? Testing direct and spillover effects of FDI," China Economic Review, Elsevier, vol. 88(C).
    21. Tadao Hoshino & Takahide Yanagi, 2024. "Causal Inference with Noncompliance and Unknown Interference," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 119(548), pages 2869-2880, October.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bpj:causin:v:1:y:2013:i:1:p:1-20:n:1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.degruyterbrill.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.