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Balancing Score Adjusted Targeted Minimum Loss-based Estimation

Author

Listed:
  • Lendle Samuel David

    (Group in Biostatistics, University of California, Berkeley, Berkeley, CA, USA)

  • Fireman Bruce

    (Division of Research, Kaiser Permanente, Oakland, CA, USA)

  • van der Laan Mark J.

    (Group in Biostatistics, University of California, Berkeley, Berkeley, CA, USA)

Abstract

Adjusting for a balancing score is sufficient for bias reduction when estimating causal effects including the average treatment effect and effect among the treated. Estimators that adjust for the propensity score in a nonparametric way, such as matching on an estimate of the propensity score, can be consistent when the estimated propensity score is not consistent for the true propensity score but converges to some other balancing score. We call this property the balancing score property, and discuss a class of estimators that have this property. We introduce a targeted minimum loss-based estimator (TMLE) for a treatment-specific mean with the balancing score property that is additionally locally efficient and doubly robust. We investigate the new estimator’s performance relative to other estimators, including another TMLE, a propensity score matching estimator, an inverse probability of treatment weighted estimator, and a regression-based estimator in simulation studies.

Suggested Citation

  • Lendle Samuel David & Fireman Bruce & van der Laan Mark J., 2015. "Balancing Score Adjusted Targeted Minimum Loss-based Estimation," Journal of Causal Inference, De Gruyter, vol. 3(2), pages 139-155, September.
    • Handle: RePEc:bpj:causin:v:3:y:2015:i:2:p:139-155:n:1
    DOI: 10.1515/jci-2012-0012
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    References listed on IDEAS

    as
    1. Kosuke Imai & David A. van Dyk, 2004. "Causal Inference With General Treatment Regimes: Generalizing the Propensity Score," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 854-866, January.
    2. Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, February.
    3. Jinyong Hahn, 1998. "On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects," Econometrica, Econometric Society, vol. 66(2), pages 315-332, March.
    Full references (including those not matched with items on IDEAS)

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