IDEAS home Printed from https://ideas.repec.org/a/bpj/causin/v3y2015i2p237-249n6.html
   My bibliography  Save this article

Propensity Score Analysis with Survey Weighted Data

Author

Listed:
  • Ridgeway Greg

    (Department of Criminology, University of Pennsylvania, 3718 Locust Walk, Philadelphia, PA 19104-6286, USA)

  • Kovalchik Stephanie Ann

    (RAND Corporation, Santa Monica, CA, USA)

  • Griffin Beth Ann

    (RAND Corporation, Santa Monica, CA, USA)

  • Kabeto Mohammed U.

    (Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA)

Abstract

Propensity score analysis (PSA) is a common method for estimating treatment effects, but researchers dealing with data from survey designs are generally not properly accounting for the sampling weights in their analyses. Moreover, recommendations given in the few existing methodological articles on this subject are susceptible to bias. We show in this article through derivation, simulation, and a real data example that using sampling weights in the propensity score estimation stage and the outcome model stage results in an estimator that is robust to a variety of conditions that lead to bias for estimators currently recommended in the statistical literature. We highly recommend researchers use the more robust approach described here. This article provides much needed rigorous statistical guidance for researchers working with survey designs involving sampling weights and using PSAs.

Suggested Citation

  • Ridgeway Greg & Kovalchik Stephanie Ann & Griffin Beth Ann & Kabeto Mohammed U., 2015. "Propensity Score Analysis with Survey Weighted Data," Journal of Causal Inference, De Gruyter, vol. 3(2), pages 237-249, September.
    • Handle: RePEc:bpj:causin:v:3:y:2015:i:2:p:237-249:n:6
    DOI: 10.1515/jci-2014-0039
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/jci-2014-0039
    Download Restriction: no
    File URL: https://libkey.io/10.1515/jci-2014-0039?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. Little R.J., 2004. "To Model or Not To Model? Competing Modes of Inference for Finite Population Sampling," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 546-556, January.
    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. Kunihama, T. & Herring, A.H. & Halpern, C.T. & Dunson, D.B., 2016. "Nonparametric Bayes modeling with sample survey weights," Statistics & Probability Letters, Elsevier, vol. 113(C), pages 41-48.
    2. Marivoet, Wim & De Herdt, Tom, 2017. "From figures to facts: making sense of socio-economic surveys in the Democratic Republic of the Congo (DRC)," IOB Analyses & Policy Briefs 23, Universiteit Antwerpen, Institute of Development Policy (IOB).
    3. J. Andrew Royle, 2009. "Analysis of Capture–Recapture Models with Individual Covariates Using Data Augmentation," Biometrics, The International Biometric Society, vol. 65(1), pages 267-274, March.
    4. David Kaplan & Chansoon Lee, 2018. "Optimizing Prediction Using Bayesian Model Averaging: Examples Using Large-Scale Educational Assessments," Evaluation Review, , vol. 42(4), pages 423-457, August.
    5. Bijak Jakub & Bryant Johan & Gołata Elżbieta & Smallwood Steve, 2021. "Preface," Journal of Official Statistics, Sciendo, vol. 37(3), pages 533-541, September.
    6. Tenan, Simone & Rotger Vallespir, Andreu & Igual, José Manuel & Moya, Óscar & Royle, J. Andrew & Tavecchia, Giacomo, 2013. "Population abundance, size structure and sex-ratio in an insular lizard," Ecological Modelling, Elsevier, vol. 267(C), pages 39-47.
    7. Shixiao Zhang & Peisong Han & Changbao Wu, 2023. "Calibration Techniques Encompassing Survey Sampling, Missing Data Analysis and Causal Inference," International Statistical Review, International Statistical Institute, vol. 91(2), pages 165-192, August.
    8. 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.
    9. Geoffrey Jones & Wesley O. Johnson, 2014. "Prior Elicitation: Interactive Spreadsheet Graphics With Sliders Can Be Fun, and Informative," The American Statistician, Taylor & Francis Journals, vol. 68(1), pages 42-51, February.
    10. Robert M. Groves & Steven G. Heeringa, 2006. "Responsive design for household surveys: tools for actively controlling survey errors and costs," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(3), pages 439-457, July.
    11. Lukachko, Alicia & Hatzenbuehler, Mark L. & Keyes, Katherine M., 2014. "Structural racism and myocardial infarction in the United States," Social Science & Medicine, Elsevier, vol. 103(C), pages 42-50.
    12. Alice Bartolini & Rosa Maria Di Biase & Lorenzo Fattorini & Sara Franceschi & Agnese Marcelli, 2021. "Design-based mapping of plant species presence, association and richness by nearest-neighbor interpolation," Department of Economics University of Siena 854, Department of Economics, University of Siena.
    13. Ivan Faiella, 2010. "The use of survey weights in regression analysis," Temi di discussione (Economic working papers) 739, Bank of Italy, Economic Research and International Relations Area.
    14. Ciro Velasco-Cruz & Luis Fernando Contreras-Cruz & Eric P. Smith & José E. Rodríguez, 2016. "A Varying Coefficients Model For Estimating Finite Population Totals: A Hierarchical Bayesian Approach," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 21(3), pages 548-568, September.
    15. Malay Ghosh, 2012. "Finite population sampling: a model-design synthesis," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 13(2), pages 235-242, June.
    16. Jan Kordos, 2016. "Development Of Smallarea Estimation In Official Statistics," Statistics in Transition New Series, Polish Statistical Association, vol. 17(1), pages 105-132, March.
    17. Rosa Maria Di Biase & Lorenzo Fattorini & Sara Franceschi & Mirko Grotti & Nicola Puletti & Piermaria Corona, 2022. "From model selection to maps: A completely design‐based data‐driven inference for mapping forest resources," Environmetrics, John Wiley & Sons, Ltd., vol. 33(7), November.
    18. repec:csb:stintr:v:17:y:2016:i:1:p:105-132 is not listed on IDEAS
    19. Christophe Quentin Valvason & Stefan Sperlich, 2024. "A Note on Simultaneous Confidence Intervals for Direct, Indirect and Synthetic Estimators," Stats, MDPI, vol. 7(1), pages 1-17, March.
    20. Brady T West & Joseph W Sakshaug & Guy Alain S Aurelien, 2016. "How Big of a Problem is Analytic Error in Secondary Analyses of Survey Data?," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-29, June.
    21. Parcel Joshua D. & Schroeter John R. & Azzam Azzeddine M, 2017. "A Re-Examination of Multistage Economies in Hog Farming," Journal of Agricultural & Food Industrial Organization, De Gruyter, vol. 15(2), pages 1-15, December.

    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:3:y:2015:i:2:p:237-249:n:6. 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.