Causal Inference using Multivariate Generalized Propensity Score R package mvGPS version 1.2.2 CRAN Task View: CausalInference (https://CRAN.R-project.org/view=CausalInference) 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. Software Depends: R (>= 3.6) Imports: Rdpack, MASS, WeightIt, cobalt, matrixNormal, geometry, sp, gbm, CBPS Suggests: testthat, knitr, dagitty, ggdag, dplyr, rmarkdown, ggplot2 Justin Williams <williazo@ucla.edu> Comprehensive R Archive Network (CRAN) Justin Williams [aut, cre] (ORCID: <https://orcid.org/0000-0002-5045-2764>) MIT + file LICENSE (https://CRAN.R-project.org/package=mvGPS/LICENSE) 2021-12-07 application/tgz https://CRAN.R-project.org/package=mvGPS doi:10.32614/CRAN.package.mvGPS