[aut, cre]Methods for estimating weights and generalized propensity score for multiple continuous exposures via the generalized propensity score described in Williams, J.R, and Cresi, C.M (2020) <arxiv:2008.13767>. Weights are constructed assuming an underlying multivariate normal density for the marginal and conditional distribution of exposures given a set of confounders. These weights can then be used to estimate dose-response curves or surfaces. This method achieves balance across all exposure dimension rather than along a single dimension.
| Version: | 1.0.2 |
| Depends: | R (≥ 3.6) |
| Imports: | Rdpack, MASS, WeightIt, cobalt, matrixNormal, geometry, sp, gbm, CBPS |
| Suggests: | testthat, knitr, dagitty, ggdag, dplyr, rmarkdown |
| Published: | 2020-09-17 |
| Author: | Justin Williams
[aut, cre] |
| Maintainer: | Justin Williams <williazo at ucla.edu> |
| BugReports: | https://github.com/williazo/mvGPS/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/williazo/mvGPS |
| NeedsCompilation: | no |
| Citation: | mvGPS citation info |
| Materials: | NEWS |
| CRAN checks: | mvGPS results |
| Reference manual: | mvGPS.pdf |
| Vignettes: |
mvGPS-intro |
| Package source: | mvGPS_1.0.2.tar.gz |
| Windows binaries: | r-devel: mvGPS_1.0.2.zip, r-release: mvGPS_1.0.2.zip, r-oldrel: mvGPS_1.0.2.zip |
| macOS binaries: | r-release: mvGPS_1.0.2.tgz, r-oldrel: mvGPS_1.0.2.tgz |
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