2020-07-31 02:09:26 UTC; Gonzalo Vazquez-Bare

2021-06-15 00:07:06 UTC; Gonzalo Vazquez-Bare

2021-07-08 00:26:50 UTC; Gonzalo Vazquez-Bare

Analysis of RD Designs with Multiple Cutoffs or Scores
The regression discontinuity (RD) design is a popular quasi-experimental design for causal inference and policy evaluation. The 'rdmulti' package provides tools to analyze RD designs with multiple cutoffs or scores: rdmc() estimates pooled and cutoff specific effects for multi-cutoff designs, rdmcplot() draws RD plots for multi-cutoff designs and rdms() estimates effects in cumulative cutoffs or multi-score designs. See Cattaneo, Titiunik and Vazquez-Bare (2018) <https://sites.google.com/site/rdpackages/rdmulti/Cattaneo-Titiunik-VazquezBare_2018_rdmulti.pdf> for further methodological details.

The regression discontinuity (RD) design is a popular quasi-experimental design for causal inference and policy evaluation. The 'rdmulti' package provides tools to analyze RD designs with multiple cutoffs or scores: rdmc() estimates pooled and cutoff specific effects for multi-cutoff designs, rdmcplot() draws RD plots for multi-cutoff designs and rdms() estimates effects in cumulative cutoffs or multi-score designs. See Cattaneo, Titiunik and Vazquez-Bare (2019) <https://sites.google.com/site/rdpackages/rdmulti/Cattaneo-Titiunik-VazquezBare_2019_rdmulti.pdf> for further methodological details.

The regression discontinuity (RD) design is a popular quasi-experimental design for causal inference and policy evaluation. The 'rdmulti' package provides tools to analyze RD designs with multiple cutoffs or scores: rdmc() estimates pooled and cutoff specific effects for multi-cutoff designs, rdmcplot() draws RD plots for multi-cutoff designs and rdms() estimates effects in cumulative cutoffs or multi-score designs. See Cattaneo, Titiunik and Vazquez-Bare (2020) <https://sites.google.com/site/rdpackages/rdmulti/Cattaneo-Titiunik-VazquezBare_2020_Stata.pdf> for further methodological details.
2020-04-22 22:37:01 UTC; Gonzalo Vazquez-Bare