# rdlocrand v0.7

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## Local Randomization Methods for RD Designs

The regression discontinuity (RD) design is a popular quasi-experimental design for causal inference and policy evaluation. Under the local randomization approach, RD designs can be interpreted as randomized experiments inside a window around the cutoff. This package provides tools to perform randomization inference for RD designs under local randomization: rdrandinf() to perform hypothesis testing using randomization inference, rdwinselect() to select a window around the cutoff in which randomization is likely to hold, rdsensitivity() to assess the sensitivity of the results to different window lengths and null hypotheses and rdrbounds() to construct Rosenbaum bounds for sensitivity to unobserved confounders. See Cattaneo, Titiunik and Vazquez-Bare (2016) <https://sites.google.com/site/rdpackages/rdlocrand/Cattaneo-Titiunik-VazquezBare_2016_Stata.pdf> for further methodological details.

## Functions in rdlocrand

 Name Description rdlocrand-package rdlocrand: Local Randomization Methods for RD Designs rdrbounds Rosenbaum bounds for RD designs under local randomization rdsensitivity Sensitivity analysis for RD designs under local randomization rdwinselect Window selection for RD designs under local randomization rdrandinf Randomization Inference for RD Designs under Local Randomization No Results!