Sensitivity Analysis for Unmeasured Confounding in Meta-Analyses.

ABSTRACT: Random-effects meta-analyses of observational studies can produce biased estimates if the synthesized studies are subject to unmeasured confounding. We propose sensitivity analyses quantifying the extent to which unmeasured confounding of specified magnitude could reduce to below a certain threshold the proportion of true effect sizes that are scientifically meaningful. We also develop converse methods to estimate the strength of confounding capable of reducing the proportion of scientifically meaningful true effects to below a chosen threshold. These methods apply when a "bias factor" is assumed to be normally distributed across studies or is assessed across a range of fixed values. Our estimators are derived using recently proposed sharp bounds on confounding bias within a single study t

SUBMITTER: Mathur MB 

PROVIDER: S-EPMC7518377 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature