IDEAS home Printed from https://ideas.repec.org/a/sae/jedbes/v42y2017i3p308-340.html
   My bibliography  Save this article

A Weighting Method for Assessing Between-Site Heterogeneity in Causal Mediation Mechanism

Author

Listed:
  • Xu Qin
  • Guanglei Hong

Abstract

When a multisite randomized trial reveals between-site variation in program impact, methods are needed for further investigating heterogeneous mediation mechanisms across the sites. We conceptualize and identify a joint distribution of site-specific direct and indirect effects under the potential outcomes framework. A method-of-moments procedure incorporating ratio-of-mediator-probability weighting (RMPW) consistently estimates the causal parameters. This strategy conveniently relaxes the assumption of no Treatment × Mediator interaction while greatly simplifying the outcome model specification without invoking strong distributional assumptions. We derive asymptotic standard errors that reflect the sampling variability of the estimated weight. We also offer an easy-to-use R package, MultisiteMediation , that implements the proposed method. It is freely available at the Comprehensive R Archive Network ( http://cran.r-project.org/web/packages/MultisiteMediation ).

Suggested Citation

  • Xu Qin & Guanglei Hong, 2017. "A Weighting Method for Assessing Between-Site Heterogeneity in Causal Mediation Mechanism," Journal of Educational and Behavioral Statistics, , vol. 42(3), pages 308-340, June.
  • Handle: RePEc:sae:jedbes:v:42:y:2017:i:3:p:308-340
    DOI: 10.3102/1076998617694879
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.3102/1076998617694879
    Download Restriction: no

    File URL: https://libkey.io/10.3102/1076998617694879?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. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. Newey, Whitney K., 1984. "A method of moments interpretation of sequential estimators," Economics Letters, Elsevier, vol. 14(2-3), pages 201-206.
    3. 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.
    4. Tyler J. Vanderweele & Guanglei Hong & Stephanie M. Jones & Joshua L. Brown, 2013. "Mediation and Spillover Effects in Group-Randomized Trials: A Case Study of the 4Rs Educational Intervention," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(502), pages 469-482, June.
    5. Garrett M. Fitzmaurice & Stuart R. Lipsitz & Joseph G. Ibrahim, 2007. "A Note on Permutation Tests for Variance Components in Multilevel Generalized Linear Mixed Models," Biometrics, The International Biometric Society, vol. 63(3), pages 942-946, September.
    6. Jeffrey R Kling & Jeffrey B Liebman & Lawrence F Katz, 2007. "Experimental Analysis of Neighborhood Effects," Econometrica, Econometric Society, vol. 75(1), pages 83-119, January.
    7. Guanglei Hong & Jonah Deutsch & Heather D. Hill, 2015. "Ratio-of-Mediator-Probability Weighting for Causal Mediation Analysis in the Presence of Treatment-by-Mediator Interaction," Mathematica Policy Research Reports 328b045b48b14d9ea3f7d0fe9, Mathematica Policy Research.
    8. 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.
    9. Carlos A. Flores & Alfonso Flores-Lagunes, 2013. "Partial Identification of Local Average Treatment Effects With an Invalid Instrument," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(4), pages 534-545, October.
    10. repec:mpr:mprres:1966 is not listed on IDEAS
    11. Jeffrey M. Albert & Suchitra Nelson, 2011. "Generalized Causal Mediation Analysis," Biometrics, The International Biometric Society, vol. 67(3), pages 1028-1038, September.
    12. Imai, Kosuke & Yamamoto, Teppei, 2013. "Identification and Sensitivity Analysis for Multiple Causal Mechanisms: Revisiting Evidence from Framing Experiments," Political Analysis, Cambridge University Press, vol. 21(2), pages 141-171, April.
    13. Terry Johnson & Mark Gritz & Russell Jackson & John Burghardt & Carol Boussy & Jan Leonard & Carlyn Orians, 1999. "National Job Corps Study: Report on the Process Analysis," Mathematica Policy Research Reports efc0cd05f0524a049779f797f, Mathematica Policy Research.
    14. repec:mpr:mprres:1968 is not listed on IDEAS
    15. Michael J. Weiss & Howard S. Bloom & Thomas Brock, 2014. "A Conceptual Framework For Studying The Sources Of Variation In Program Effects," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 33(3), pages 778-808, June.
    Full references (including those not matched with items on IDEAS)

    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. Xu Qin & Jonah Deutsch & Guanglei Hong, 2021. "Unpacking Complex Mediation Mechanisms And Their Heterogeneity Between Sites In A Job Corps Evaluation," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 40(1), pages 158-190, January.
    2. Martin Huber & Michael Lechner & Giovanni Mellace, 2016. "The Finite Sample Performance of Estimators for Mediation Analysis Under Sequential Conditional Independence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 139-160, January.
    3. Guanglei Hong & Fan Yang & Xu Qin, 2023. "Posttreatment confounding in causal mediation studies: A cutting‐edge problem and a novel solution via sensitivity analysis," Biometrics, The International Biometric Society, vol. 79(2), pages 1042-1056, June.
    4. Martin Huber, 2015. "Causal Pitfalls in the Decomposition of Wage Gaps," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 179-191, April.
    5. Davide Viviano, 2020. "Experimental Design under Network Interference," Papers 2003.08421, arXiv.org, revised Jul 2022.
    6. Huber, Martin, 2012. "Identifying causal mechanisms in experiments (primarily) based on inverse probability weighting," Economics Working Paper Series 1213, University of St. Gallen, School of Economics and Political Science, revised May 2013.
    7. Anup Malani & Cynthia Kinnan & Gabriella Conti & Kosuke Imai & Morgen Miller & Shailender Swaminathan & Alessandra Voena & Bartosz Woda, 2024. "Evaluating pricing health insurance in lower-income countries: A field experiment in India," IFS Working Papers W24/33, Institute for Fiscal Studies.
    8. Michel Dumont & Glenn Rayp & Olivier Thas & Peter Willemé, 2005. "Correcting Standard Errors in Two‐stage Estimation Procedures with Generated Regressands," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(3), pages 421-433, June.
    9. Christian Dippel & Robert Gold & Stephan Heblich & Rodrigo Pinto, 2017. "Instrumental Variables and Causal Mechanisms: Unpacking the Effect of Trade on Workers and Voters," CESifo Working Paper Series 6816, CESifo.
    10. Martin Huber & Yu‐Chin Hsu & Ying‐Ying Lee & Layal Lettry, 2020. "Direct and indirect effects of continuous treatments based on generalized propensity score weighting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(7), pages 814-840, November.
    11. 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.
    12. Martin Huber & Michael Lechner & Giovanni Mellace, 2017. "Why Do Tougher Caseworkers Increase Employment? The Role of Program Assignment as a Causal Mechanism," The Review of Economics and Statistics, MIT Press, vol. 99(1), pages 180-183, March.
    13. Patrick Fève & Alain Guay, 2009. "The Response of Hours to a Technology Shock: A Two‐Step Structural VAR Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(5), pages 987-1013, August.
    14. Amengual, Dante & Fiorentini, Gabriele & Sentana, Enrique, 2013. "Sequential estimation of shape parameters in multivariate dynamic models," Journal of Econometrics, Elsevier, vol. 177(2), pages 233-249.
    15. Malani, Anup & Kinnan, Cynthia & Conti, Gabriella & Imai, Kosuke & Miller, Morgen & Swaminathan, Shailender & Voena, Alessandra & Woda, Bartek, 2024. "Evaluating and pricing health insurance in lower-income countries: A field experiment in India," CEPR Discussion Papers 19326, C.E.P.R. Discussion Papers.
    16. 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.
    17. Arnab Bhattacharjee & Sean Holly, 2013. "Understanding Interactions in Social Networks and Committees," Spatial Economic Analysis, Taylor & Francis Journals, vol. 8(1), pages 23-53, March.
    18. Denis Fougère & Nicolas Jacquemet, 2020. "Policy Evaluation Using Causal Inference Methods," SciencePo Working papers Main hal-03455978, HAL.
    19. Adrian C. Darnell, 1994. "A Dictionary Of Econometrics," Books, Edward Elgar Publishing, number 118.
    20. Victor Aguirregabiria & Pedro Mira, 2002. "Swapping the Nested Fixed Point Algorithm: A Class of Estimators for Discrete Markov Decision Models," Econometrica, Econometric Society, vol. 70(4), pages 1519-1543, July.

    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:sae:jedbes:v:42:y:2017:i:3:p:308-340. 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: SAGE Publications (email available below). General contact details of provider: .

    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.