Estimating the causal effects of exposure mixtures: a generalized propensity score method.

ABSTRACT:

Background

In environmental epidemiology and many other fields, estimating the causal effects of multiple concurrent exposures holds great promise for driving public health interventions and policy changes. Given the predominant reliance on observational data, confounding remains a key consideration, and generalized propensity score (GPS) methods are widely used as causal models to control measured confounders. However, current GPS methods for multiple continuous exposures remain scarce.

Methods

We proposed a novel causal model for exposure mixtures, called nonparametric multivariate covariate balancing generalized propensity score (npmvCBGPS). A simulation study examined whether npmvCBGPS, an existing multivariate GPS (mvGPS) method, and a linear regression model for the ou

SUBMITTER: Gao Q 

PROVIDER: S-EPMC12482879 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature