Generalized meta-analysis for multiple regression models across studies with disparate covariate information.
We describe extensions of the iterated reweighted least-squares algorithm for fitting generalized linear regression models using the proposed framework. Based on the same moment equations, we also develop a diagnostic test for detecting violations of underlying model assumptions, such as those arising from heterogeneity in the underlying study populations. The proposed methods are illustrated with extensive simulation studies and a real-data example involving the development of a breast cancer risk prediction model using disparate risk factor information from multiple studies.
PMID: 31427822 [PubMed]
Source: Biometrika - Category: Biotechnology Authors: Kundu P, Tang R, Chatterjee N Tags: Biometrika Source Type: research
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