Fast procedures for small set of commonly-used, design-appropriate estimators with robust standard errors and confidence intervals. Includes estimators for linear regression, instrumental variables regression, difference-in-means, Horvitz-Thompson estimation, and regression improving precision of experimental estimates by interacting treatment with centered pre-treatment covariates introduced by Lin (2013) <doi:10.1214/12-AOAS583>.
| Version: |
0.12 |
| Depends: |
R (≥ 3.4.0) |
| Imports: |
Rcpp (≥ 0.12.16), methods, Formula, rlang (≥ 0.2.0) |
| LinkingTo: |
Rcpp, RcppEigen |
| Suggests: |
RcppEigen, fabricatr (≥ 0.4), randomizr (≥ 0.16), testthat, sandwich, clubSandwich, margins, prediction, lfe, AER, ivpack, stargazer, car |
| Enhances: |
broom, texreg |
| Published: |
2018-09-15 |
| Author: |
Graeme Blair [aut, cre],
Jasper Cooper [aut],
Alexander Coppock [aut],
Macartan Humphreys [aut],
Luke Sonnet [aut],
Neal Fultz [ctb] |
| Maintainer: |
Graeme Blair <graeme.blair at ucla.edu> |
| BugReports: |
https://github.com/DeclareDesign/estimatr/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://declaredesign.org/r/estimatr/,
https://github.com/DeclareDesign/estimatr |
| NeedsCompilation: |
yes |
| Materials: |
NEWS |
| CRAN checks: |
estimatr results |