Monte Carlo Simulation Approaches for Quantitative Bias Analysis: A Tutorial.

ABSTRACT: Quantitative bias analysis can be used to empirically assess how far study estimates are from the truth (i.e., an estimate that is free of bias). These methods can be used to explore the potential impact of confounding bias, selection bias (collider stratification bias), and information bias. Quantitative bias analysis includes methods that can be used to check the robustness of study findings to multiple types of bias and methods that use simulation studies to generate data and understand the hypothetical impact of specific types of bias in a simulated data set. In this article, we review 2 strategies for quantitative bias analysis: 1) traditional probabilistic quantitative bias analysis and 2) quantitative bias analysis with generated data. An important difference between the 2 strategie

SUBMITTER: Banack HR 

PROVIDER: S-EPMC9005059 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature