Journal of Statistical Software · 2011 · 4.4K citations · 19 references
Public HealthBiostatisticsCausal InferenceEconometricsStatistical ModelingCausal Effect EstimationData AnalysisMatching MethodsNonparametric EconometricsNonparametric StatisticsPropensity Score MethodsCausal Inference From DataMatchingParametric Regression ModelsRobustnessWithin-group Matching
<b>MatchIt</b> implements the suggestions of Ho, Imai, King, and Stuart (2007) for improving parametric statistical models by preprocessing data with nonparametric matching methods. <b>MatchIt</b> 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 <b>MatchIt</b>, researchers can use whatever parametric model they would have used without <b>MatchIt</b>, but produce inferences with substantially more robustness and less sensitivity to modeling assumptions. <b>MatchIt</b> is an R program, and also works seamlessly with <b>Zelig</b>.
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Classification and Regression Trees.
Alexander Gordon, Leo Breiman, Jerome H. Friedman et al. · Biometrics · 1984 · 23.9K citations
Richard A. Brown, Trevor Hastie, Robert Tibshirani · Biometrics · 1991 · 8.3K citations