Why Propensity Scores Should Not Be Used for Matching

  title={Why Propensity Scores Should Not Be Used for Matching},
  author={Gary King and Richard A. Nielsen},
  journal={Political Analysis},
  pages={435 - 454}
We show that propensity score matching (PSM), an enormously popular method of preprocessing data for causal inference, often accomplishes the opposite of its intended goal—thus increasing imbalance, inefficiency, model dependence, and bias. The weakness of PSM comes from its attempts to approximate a completely randomized experiment, rather than, as with other matching methods, a more efficient fully blocked randomized experiment. PSM is thus uniquely blind to the often large portion of… 

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Improving Causal Inference in Observational Studies: Propensity Score Matching

  • M. YuD. Kang
  • Psychology
    Cardiovascular Prevention and Pharmacotherapy
  • 2019
The concept of PSM, PSM methods, limitations, and statistical tools are introduced, and the conditional probabilities that individuals will be included in the experimental group when covariates are controlled for all subjects are reflected.

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Sensitivity of Propensity Score Methods to the Specifications

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