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rdrobust

Statistical inference and graphical procedures for RD designs using local polynomial and partitioning regression methods.

https://github.com/rdpackages/rdrobust

Science Score: 36.0%

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    CITATION.cff file
  • ✓
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    Committers with academic emails
    1 of 1 committers (100.0%) from academic institutions
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    Scientific vocabulary similarity
    Low similarity (12.1%) to scientific vocabulary

Keywords

causal-inference program-evaluation regression-discontinuity-designs treatment-effects
Last synced: 10 months ago · JSON representation

Repository

Statistical inference and graphical procedures for RD designs using local polynomial and partitioning regression methods.

Basic Info
  • Host: GitHub
  • Owner: rdpackages
  • License: other
  • Language: Stata
  • Default Branch: master
  • Homepage:
  • Size: 10.2 MB
Statistics
  • Stars: 85
  • Watchers: 5
  • Forks: 39
  • Open Issues: 0
  • Releases: 0
Topics
causal-inference program-evaluation regression-discontinuity-designs treatment-effects
Created almost 6 years ago · Last pushed 12 months ago
Metadata Files
Readme License

README.md

RDROBUST

The rdrobust package provides Python, R and Stata implementations of statistical inference and graphical procedures for Regression Discontinuity designs employing local polynomial and partitioning methods. It provides point estimators, confidence intervals estimators, bandwidth selectors, automatic RD plots, and many other features.

This work was supported in part by the National Science Foundation through grants SES-1357561, SES-1459931, SES-1947805, and SES-2019432.

Website

https://rdpackages.github.io/rdrobust

Queries and Requests

Please email: rdpackages@googlegroups.com

Major Upgrades

This package was first released in Spring 2014, and had two major upgrades in Fall 2016 and in Winter 2020.

  • Fall 2016 new features include: (i) major speed improvements; (ii) covariate-adjusted bandwidth selection, point estimation, and robust inference; (iii) cluster-robust bandwidth selection, point estimation, and robust inference; (iv) weighted global polynomial fits and pointwise confidence bands for RD plots; and (v) several new bandwidths selectors (e.g., different bandwidths for control and treatment groups, coverage error optimal bandwidths, and optimal bandwidths for fuzzy designs).

  • Winter 2020 new features include: (i) discrete running variable checks and adjustments; (ii) bandwidth selection adjustments for too few mass points in and/or overshooting of the support of the running variable; (iii) RD Plots with additional covariates plotted at their mean (previously the package set additional covariates at zero); (iv) automatic removal of co-linear additional covariates; (v) turn on/off standardization of variables (which may lead to small numerical/rounding discrepancies with prior versions); and (vi) rdplot output using ggplot2 in R.

Python Implementation

To install/update in Python type: pip install rdrobust

R Implementation

To install/update in R type: install.packages('rdrobust')

Stata Implementation

To install/update in Stata type: net install rdrobust, from(https://raw.githubusercontent.com/rdpackages/rdrobust/master/stata) replace

References

For overviews and introductions, see rdpackages website.

Software and Implementation

Technical and Methodological



Owner

  • Name: RD Packages
  • Login: rdpackages
  • Kind: organization

Regression Discontinuity Designs

GitHub Events

Total
  • Watch event: 12
  • Push event: 4
  • Fork event: 1
Last Year
  • Watch event: 12
  • Push event: 4
  • Fork event: 1

Committers

Last synced: over 2 years ago

All Time
  • Total Commits: 91
  • Total Committers: 1
  • Avg Commits per committer: 91.0
  • Development Distribution Score (DDS): 0.0
Past Year
  • Commits: 9
  • Committers: 1
  • Avg Commits per committer: 9.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Matias D. Cattaneo c****o@p****u 91
Committer Domains (Top 20 + Academic)
princeton.edu: 1

Issues and Pull Requests

Last synced: 11 months ago

All Time
  • Total issues: 0
  • Total pull requests: 7
  • Average time to close issues: N/A
  • Average time to close pull requests: 4 months
  • Total issue authors: 0
  • Total pull request authors: 7
  • Average comments per issue: 0
  • Average comments per pull request: 1.0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
Pull Request Authors
  • niwreg-coder (1)
  • wbuchanan (1)
  • droodman (1)
  • xiapo00 (1)
  • ozak (1)
  • connorp (1)
  • danielcsaba (1)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 210,543 last-month
  • Total dependent packages: 2
  • Total dependent repositories: 1
  • Total versions: 15
  • Total maintainers: 2
pypi.org: rdrobust

Implements local polynomial Regression Discontinuity (RD) point estimators with robust bias-corrected confidence intervals and inference procedures.

  • Versions: 15
  • Dependent Packages: 2
  • Dependent Repositories: 1
  • Downloads: 210,543 Last month
Rankings
Dependent packages count: 3.2%
Forks count: 6.6%
Stargazers count: 9.0%
Downloads: 9.7%
Average: 10.0%
Dependent repos count: 21.5%
Maintainers (2)
rmasini scalonico
Last synced: 11 months ago

Dependencies

R/rdrobust/DESCRIPTION cran
  • R >= 3.1.1 depends
  • MASS * imports
  • ggplot2 * imports
Python/rdrobust/src/rdrobust.egg-info/requires.txt pypi
  • numpy *
  • pandas *
  • plotnine *
  • scipy *
  • sklearn *