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arXiv · 2409.13458

Interpretable meta-analysis of model or marker performance

Jon A. Steingrimsson·Lan Wen·Sarah Voter·Issa J. Dahabreh
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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.

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Jon A. Steingrimsson, Lan Wen, Sarah Voter, Issa J. Dahabreh. 2024-09-20. Interpretable meta-analysis of model or marker performance. https://arxiv.org/abs/2409.13458

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