A repeated measures approach to pooled and calibrated biomarker data.

ABSTRACT: Participant-level meta-analysis across multiple studies increases the sample size for pooled analyses, thereby improving precision in effect estimates and enabling subgroup analyses. For analyses involving biomarker measurements as an exposure of interest, investigators must first calibrate the data to address measurement variability arising from usage of different laboratories and/or assays. In practice, the calibration process involves reassaying a random subset of biospecimens from each study at a central laboratory and fitting models that relate the study-specific "local" and central laboratory measurements. Previous work in this area treats the calibration process from the perspective of measurement error techniques and imputes the estimated central laboratory value among individuals

SUBMITTER: Sloan A 

PROVIDER: S-EPMC9986973 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature