WeightIt: Weighting for Covariate Balance in Observational Studies
Generates weights to form equivalent groups in observational studies with point or longitudinal treatments by easing and extending the functionality of the R packages 'twang' for generalized boosted modeling (McCaffrey, Ridgeway & Morral, 2004) <doi:10.1037/1082-989X.9.4.403>, 'CBPS' for covariate balancing propensity score weighting (Imai & Ratkovic, 2014) <doi:10.1111/rssb.12027>, 'ebal' for entropy balancing (Hainmueller, 2012) <doi:10.1093/pan/mpr025>, 'optweight' for optimization-based weights (Zubizarreta, 2015) <doi:10.1080/01621459.2015.1023805>, 'ATE' for empirical balancing calibration weighting (Chan, Yam, & Zhang, 2016) <doi:10.1111/rssb.12129>, and 'SuperLearner' for stacked machine learning-based propensity scores (Pirracchio, Petersen, & van der Laan, 2015) <doi:10.1093/aje/kwu253>. Also allows for assessment of weights and checking of covariate balance by interfacing directly with 'cobalt'.
| Version: |
0.7.1 |
| Depends: |
R (≥ 3.3.0) |
| Imports: |
ggplot2 (≥ 3.0.0) |
| Suggests: |
cobalt (≥ 3.9.0), twang (≥ 1.5), CBPS (≥ 0.18), ebal (≥
0.1-6), ATE (≥ 0.2.0), optweight (≥ 0.2.4), SuperLearner (≥
2.0-25), class, gam, mlogit (≥ 0.3-0), MNP (≥ 3.1-0), brglm2 (≥ 0.5.1), survey, jtools, boot, MASS, gbm (≥ 2.1.3), knitr, rmarkdown |
| Published: |
2019-10-30 |
| Author: |
Noah Greifer [aut, cre] (<https://orcid.org/0000-0003-3067-7154>) |
| Maintainer: |
Noah Greifer <noah.greifer at gmail.com> |
| BugReports: |
https://github.com/ngreifer/WeightIt/issues |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: |
https://github.com/ngreifer/WeightIt |
| NeedsCompilation: |
no |
| Materials: |
README NEWS |
| CRAN checks: |
WeightIt results |
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