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Use optimization to estimate weights that balance covariates for binary, multinomial, and continuous treatments in the spirit of Zubizarreta (2015) <doi:10.1080/01621459.2015.1023805>. The degree of balance can be specified for each covariate. In addition, sampling weights can be estimated that allow a sample to generalize to a population specified with given target moments of covariates.
| Version: | 0.2.5 |
| Depends: | R (≥ 3.4.0) |
| Imports: | osqp (≥ 0.6.0.2), Matrix (≥ 1.2-13), ggplot2 (≥ 3.0.0) |
| Suggests: | cobalt (≥ 3.8.0), twang (≥ 1.5) |
| Published: | 2019-09-16 |
| Author: | Noah Greifer [aut, cre] |
| Maintainer: | Noah Greifer <noah.greifer at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL] |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| In views: | CausalInference |
| CRAN checks: | optweight results |
| Reference manual: | optweight.pdf |
| Package source: | optweight_0.2.5.tar.gz |
| Windows binaries: | r-devel: optweight_0.2.5.zip, r-release: optweight_0.2.5.zip, r-oldrel: optweight_0.2.5.zip |
| macOS binaries: | r-release (arm64): optweight_0.2.5.tgz, r-oldrel (arm64): optweight_0.2.5.tgz, r-release (x86_64): optweight_0.2.5.tgz, r-oldrel (x86_64): optweight_0.2.5.tgz |
| Old sources: | optweight archive |
| Reverse suggests: | cobalt, jointVIP, WeightIt |
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