2024/09/20 by Jon A. Steingrimsson, Lan Wen, Steingrimsson, Jon A. +5
Engineering · #Engineering Applied Research
paper · pdf · doi:10.48550/arxiv.2409.13458
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.