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New method distinguishes case-mix from context heterogeneity in prognostic models

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Researchers have developed a new method to distinguish between case-mix and context heterogeneity in prognostic regression models, particularly when synthesizing data from multiple sites. The approach involves fitting site-specific local regressions in a dimension-reduced space, partitioning the smoothed coefficient surfaces into a cross-site reference and site-specific deviations. This diagnostic distinction helps determine whether joint or site-specific regression models are more appropriate for analysis, as demonstrated on a chronic obstructive pulmonary disease trial. AI

RANK_REASON The cluster contains a single academic paper published on arXiv. [lever_c_demoted from research: ic=1 ai=0.4]

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New method distinguishes case-mix from context heterogeneity in prognostic models

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The cluster contains a single academic paper published on arXiv. [lever_c_demoted from research: ic=1 ai=0.4]
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COVERAGE [1]

  1. arXiv stat.ML TIER_1 English(EN) · Max Behrens, Janis M. Nolde, Eleni Papakonstantinou, Gabriele Bellerino, Theodoros Evrenoglou, Angelika Rohde, Daiana Stolz, Moritz Hess, Harald Binder ·

    Distinguishing case-mix from context heterogeneity in prognostic regression model synthesis settings

    arXiv:2608.12885v1 Announce Type: cross Abstract: Prognostic regression models often synthesize data from multiple sites, whether within a multi-site study, across federated settings, or in individual participant data meta-analysis. Here, a site is any data source, such as a hosp…

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