Weighting regressions by propensity scores.

  title={Weighting regressions by propensity scores.},
  author={David A. Freedman and Richard A. Berk},
  journal={Evaluation review},
  volume={32 4},
Regressions can be weighted by propensity scores in order to reduce bias. However, weighting is likely to increase random error in the estimates, and to bias the estimated standard errors downward, even when selection mechanisms are well understood. Moreover, in some cases, weighting will increase the bias in estimated causal parameters. If investigators have a good causal model, it seems better just to fit the model without weights. If the causal model is improperly specified, there can be… CONTINUE READING

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Propensity Score Matching: A Note of Caution for Evaluators of Social Programs,

  • D. N. Peikes, L. Moreno, S. M. Orzol
  • The American Statistician,
  • 2008
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Some General Theory for Weighted Regressions,

  • D. A. Freedman
  • 2008
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