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A Weighting Analogue to Pair Matching in Propensity Score Analysis

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  • Li Liang

    () (Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, Texas, USA)

  • Greene Tom

    () (Division of Epidemiology, University of Utah, Salt Lake City, Utah, USA)

Abstract

Propensity score (PS) matching is widely used for studying treatment effects in observational studies. This article proposes the method of matching weights (MWs) as an analog to one-to-one pair matching without replacement on the PS with a caliper. Compared with pair matching, the proposed method offers more efficient estimation, more accurate variance calculation, better balance, and simpler asymptotic analysis. A statistical test for the misspecification of the PS model is proposed for balance checking purposes. An augmented version of the MW estimator is developed that has the double robust property, that is, the estimator is consistent, if either the outcome model or the PS model is correct. The proposed method is studied in simulations and illustrated through a real data example.

Suggested Citation

  • Li Liang & Greene Tom, 2013. "A Weighting Analogue to Pair Matching in Propensity Score Analysis," The International Journal of Biostatistics, De Gruyter, vol. 9(2), pages 215-234, July.
  • Handle: RePEc:bpj:ijbist:v:9:y:2013:i:2:p:215-234:n:4
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    References listed on IDEAS

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    1. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2009. "Dealing with limited overlap in estimation of average treatment effects," Biometrika, Biometrika Trust, vol. 96(1), pages 187-199.
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    5. Ho, Daniel E. & Imai, Kosuke & King, Gary & Stuart, Elizabeth A., 2007. "Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference," Political Analysis, Cambridge University Press, vol. 15(03), pages 199-236, June.
    6. David A. Freedman & Richard A. Berk, 2008. "Weighting Regressions by Propensity Scores," Evaluation Review, , vol. 32(4), pages 392-409, August.
    7. Weihua Cao & Anastasios A. Tsiatis & Marie Davidian, 2009. "Improving efficiency and robustness of the doubly robust estimator for a population mean with incomplete data," Biometrika, Biometrika Trust, vol. 96(3), pages 723-734.
    8. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
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