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mvGPS (version 1.2.2)

Causal Inference using Multivariate Generalized Propensity Score

Description

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) . 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.

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install.packages('mvGPS')

Monthly Downloads

257

Version

1.2.2

License

MIT + file LICENSE

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Maintainer

Justin Williams

Last Published

December 7th, 2021

Functions in mvGPS (1.2.2)

mvGPS

Multivariate Generalized Propensity Score
hull_sample

Sample Points Along a Convex Hull
D_C_check

Internal function for formatting and checking specification of exposures and confounders
gen_D

Generate Bivariate Multivariate Exposure
bal

Construct Covariate Balance Statistics for Models with Multivariate Exposure
X_check

Checking that the exposure matrix is properly specified