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Replication data for: Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference Aug 20, 2014 - Gary King Dataverse Ho, Daniel E.; Imai, Kosuke; King, Gary; Stuart, Elizabeth A., 2007, "Replication data for: Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference", https://doi.org/10.7910/DVN/RWUY8G, Harvard Dataverse, V5, UNF:3:QV0mYCd8eV+mJgWDnYct5g== [fileUNF] Although published works rarely include causal estimates from more than a few model specifications, authors usually choose the presented estimates from numerous trial runs readers never see. Given the often large variation in estimates across choices of control variables, functional forms, and other modeling assumptions, how can researchers ensure...

Replication data for: Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference

Aug 20, 2014 - Gary King Dataverse

Ho, Daniel E.; Imai, Kosuke; King, Gary; Stuart, Elizabeth A., 2007, "Replication data for: Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference", https://doi.org/10.7910/DVN/RWUY8G, Harvard Dataverse, V5, UNF:3:QV0mYCd8eV+mJgWDnYct5g== [fileUNF]

Although published works rarely include causal estimates from more than a few model specifications, authors usually choose the presented estimates from numerous trial runs readers never see. Given the often large variation in estimates across choices of control variables, functional forms, and other modeling assumptions, how can researchers ensure...

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