Package: mvGPS 1.2.2
mvGPS: Causal Inference using Multivariate Generalized Propensity Score
Methods for estimating and utilizing the multivariate generalized propensity score (mvGPS) for multiple continuous exposures described in Williams, J.R, and Crespi, C.M. (2020) <arxiv:2008.13767>. The methods allow estimation of a dose-response surface relating the joint distribution of multiple continuous exposure variables to an outcome. Weights are constructed assuming a multivariate normal density for the marginal and conditional distribution of exposures given a set of confounders. Confounders can be different for different exposure variables. The weights are designed to achieve balance across all exposure dimensions and can be used to estimate dose-response surfaces.
Authors:
mvGPS_1.2.2.tar.gz
mvGPS_1.2.2.zip(r-4.7-any)mvGPS_1.2.2.zip(r-4.6-any)mvGPS_1.2.2.zip(r-4.5-any)
mvGPS_1.2.2.tgz(r-4.6-any)mvGPS_1.2.2.tgz(r-4.5-any)
mvGPS_1.2.2.tar.gz(r-4.7-any)mvGPS_1.2.2.tar.gz(r-4.6-any)
mvGPS_1.2.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
mvGPS/json (API)
| # Install 'mvGPS' in R: |
| install.packages('mvGPS', repos = c('https://williazo.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/williazo/mvgps/issues
Last updated from:babf41bf51. Checks:7 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | NOTE | 160 | ||
| source / vignettes | OK | 225 | ||
| linux-release | NOTE | 172 | ||
| macos-release | NOTE | 228 | ||
| macos-oldrel | NOTE | 168 | ||
| windows-devel | NOTE | 138 | ||
| windows-release | NOTE | 121 | ||
| windows-oldrel | NOTE | 93 | ||
| wasm-release | OK | 109 |
Exports:balgen_Dhull_samplemvGPS
Dependencies:abindargCBPSclicobaltcodetoolscpp11farverforeachgbmgenericsgeometryggplot2glmnetgluegridExtragtableisobanditeratorslabelinglatticelifecyclelinproglpSolvemagicMASSMatchItMatrixmatrixNormalmvtnormnnetnumDerivR6rbibutilsRColorBrewerRcppRcppEigenRcppProgressRdpackrlangS7sandwichscalesshapespsurvivalvctrsviridisLiteWeightItwithrzoo
