Quantitative bias analysis for mismeasured variables in health research: a review of software tools.

ABSTRACT:

Background

Measurement error and misclassification can cause bias or loss of power in epidemiological studies. Software performing quantitative bias analysis (QBA) to assess the sensitivity of results to mismeasurement are available. However, QBA is still not commonly used in practice, partly due to a lack of knowledge of these software implementations. The features and particular use cases of these tools have not been systematically evaluated.

Methods

We reviewed and summarised the latest available software tools for QBA in relation to mismeasured variables in health research. We searched the electronic database Web of Science for studies published between [Formula: see text] January 2014 and [Formula: see text] May 2024 (inclusive). We included epidemiological studies that

SUBMITTER: Gerlach-Wood CJC 

PROVIDER: S-EPMC12317562 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature