articleJournal of Statistical SoftwareJan 1, 2011DIAMOND OA

MatchIt : Nonparametric Preprocessing for Parametric Causal Inference

Harvard University Press

Indexed incrossrefdoaj

Abstract

MatchIt implements the suggestions of Ho, Imai, King, and Stuart (2007) for improving parametric statistical models by preprocessing data with nonparametric matching methods. MatchIt implements a wide range of sophisticated matching methods, making it possible to greatly reduce the dependence of causal inferences on hard-to-justify, but commonly made, statistical modeling assumptions. The software also easily fits into existing research practices since, after preprocessing data with MatchIt, researchers can use whatever parametric model they would have used without MatchIt, but produce inferences with substantially more robustness and less sensitivity to modeling assumptions. MatchIt is an R program, and also…

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Authors

4

Topics & keywords

Keywords
  • Preprocessor
  • Nonparametric statistics
  • Computer science
  • Parametric statistics
  • Causal inference
  • Robustness (evolution)
  • Statistical inference
  • Parametric model
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