Stratification-based instrumental variable analysis framework for nonlinear effect analysis.

ABSTRACT: Nonlinear causal effects are prevalent in many research scenarios involving continuous exposures, and instrumental variables (IVs) can be employed to investigate such effects, particularly in the presence of unmeasured confounders. However, common IV methods for nonlinear effect analysis, such as IV regression or the control-function method, have inherent limitations, leading to either low statistical power or potentially misleading conclusions. In this work, we propose an alternative IV framework for nonlinear effect analysis, which has recently emerged in genetic epidemiology and addresses many of the drawbacks of existing IV methods. The proposed IV framework consists of up to three key "S" elements: (i) the Stratification approach, which constructs multiple strata that are sub-samples

SUBMITTER: Tian H 

PROVIDER: S-EPMC12665183 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature