Interpretable meta-analysis of model or marker performance
Methodology
2024-09-23 v1
Abstract
Conventional meta analysis of model performance conducted using datasources from different underlying populations often result in estimates that cannot be interpreted in the context of a well defined target population. In this manuscript we develop methods for meta-analysis of several measures of model performance that are interpretable in the context of a well defined target population when the populations underlying the datasources used in the meta analysis are heterogeneous. This includes developing identifiablity conditions, inverse-weighting, outcome model, and doubly robust estimator. We illustrate the methods using simulations and data from two large lung cancer screening trials.
Cite
@article{arxiv.2409.13458,
title = {Interpretable meta-analysis of model or marker performance},
author = {Jon A. Steingrimsson and Lan Wen and Sarah Voter and Issa J. Dahabreh},
journal= {arXiv preprint arXiv:2409.13458},
year = {2024}
}