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: |
1.0.0 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
Formula, generics, methods, Rcpp (≥ 0.12.16), rlang (≥
0.2.0) |
| LinkingTo: |
Rcpp, RcppEigen |
| Suggests: |
fabricatr (≥ 0.10.0), randomizr (≥ 0.20.0), AER, clubSandwich, emmeans (≥ 1.4), estimability, margins, modelsummary, prediction, RcppEigen, sandwich, stargazer, testthat, car |
| Enhances: |
texreg |
| Published: |
2022-07-04 |
| Author: |
Graeme Blair [aut, cre],
Jasper Cooper [aut],
Alexander Coppock [aut],
Macartan Humphreys [aut],
Luke Sonnet [aut],
Neal Fultz [ctb],
Lily Medina [ctb],
Russell Lenth [ctb] |
| Maintainer: |
Graeme Blair <graeme.blair at gmail.com> |
| 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 |
| In views: |
CausalInference, Econometrics |
| CRAN checks: |
estimatr results |