Measured and accounted-for confounding in pharmacoepidemiologic studies: Some thoughts for practitioners.

ABSTRACT:

Background

Valid causal inference from observational pharmacoepidemiologic studies relies on adequately adjusting for confounding.

Aims

The goal of this article is to provide clarity and guidance on issues related to confounding and provide motivation for using more flexible models for causal inference in pharmacoepidemiology.

Materials & methods

In this article we elucidate two important components of making valid inference from observational data: measuring the necessary set of variables at the design/data collection phase (measured confounding) and properly accounting for confounding at the modeling/analysis phase (accounted-for confounding). For the latter concept, we contrast parametric modeling approaches, which are susceptible to model misspecification bias, wi

SUBMITTER: Roy J 

PROVIDER: S-EPMC8635757 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature