Embedded multilevel regression and poststratification: Model-based inference with incomplete auxiliary information.

ABSTRACT: Health disparity research often evaluates health outcomes across demographic subgroups. Multilevel regression and poststratification (MRP) is a popular approach for small subgroup estimation as it can stabilize estimates by fitting multilevel models and adjust for selection bias by poststratifying on auxiliary variables, which are population characteristics predictive of the analytic outcome. However, the granularity and quality of the estimates produced by MRP are limited by the availability of the auxiliary variables' joint distribution; data analysts often only have access to the marginal distributions. To overcome this limitation, we embed the estimation of population cell counts needed for poststratification into the MRP workflow: embedded MRP (EMRP). Under EMRP, we generate synthetic

SUBMITTER: Li K 

PROVIDER: S-EPMC11418010 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature