most citedAccommodating heterogeneous missing data patterns for prostate cancer risk prediction

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stat.AP2021★ 3 cited

Accommodating heterogeneous missing data patterns for prostate cancer risk prediction

Matthias Neumair, Michael W. Kattan, Stephen J. Freedland +13

Objective: We compared six commonly used logistic regression methods for accommodating missing risk factor data from multiple heterogeneous cohorts, in which some cohorts do not co…