Causal Inference using Multivariate Generalized Propensity Score
Construct Covariate Balance Statistics for Models with Multivariate Ex...
Internal function for formatting and checking specification of exposur...
Generate Bivariate Multivariate Exposure
Sample Points Along a Convex Hull
Multivariate Generalized Propensity Score
Checking that the exposure matrix is properly specified
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.