Matching methods for causal inference: A review and a look forward.

@article{Stuart2010MatchingMF,
  title={Matching methods for causal inference: A review and a look forward.},
  author={Elizabeth A. Stuart},
  journal={Statistical science : a review journal of the Institute of Mathematical Statistics},
  year={2010},
  volume={25 1},
  pages={
          1-21
        }
}
When estimating causal effects using observational data, it is desirable to replicate a randomized experiment as closely as possible by obtaining treated and control groups with similar covariate distributions. This goal can often be achieved by choosing well-matched samples of the original treated and control groups, thereby reducing bias due to the covariates. Since the 1970's, work on matching methods has examined how to best choose treated and control subjects for comparison. Matching… CONTINUE READING

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References

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SHOWING 1-10 OF 125 REFERENCES

The performance of different propensity score methods for estimating marginal odds ratios

  • P. C. Austin
  • Stat. Med. 26 3078–3094. MR2380505
  • 2007
Highly Influential
5 Excerpts

Observational Studies, 2nd ed

  • P. R. Rosenbaum
  • Springer, New York. MR1899138
  • 2002
Highly Influential
6 Excerpts

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