Joint Indirect Standardization when Only Marginal Distributions are Observed in the Index Population.

ABSTRACT: It is a common interest in medicine to determine whether a hospital meets a benchmark created from an aggregate reference population, after accounting for differences in distributions of multiple covariates. Due to the difficulties of collecting individual-level data, however, it is often the case that only marginal distributions of the covariates are available, making covariate-adjusted comparison challenging. We propose and evaluate a novel approach for conducting indirect standardization when only marginal covariate distributions of the studied hospital are known, but complete information is available for the reference hospitals. We do this with the aid of two existing methods: iterative proportional fit, which estimates the cells of a contingency table when only marginal sums are known

SUBMITTER: Wang Y 

PROVIDER: S-EPMC6710018 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature