Modeling Strategies for Risk Prediction in Clinical Medicine with Restricted Data: Application to Cardiovascular Disease

Junyoung Lee () and Wai Kin (Victor) Chan ()
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Junyoung Lee: Tsinghua University
Wai Kin (Victor) Chan: Tsinghua University

A chapter in LISS 2020, 2021, pp 13-29 from Springer

Abstract: Abstract This paper describes modeling strategies for risk prediction in clinical medicine, mainly with respect to survival analysis. Restricted data, which is commonly given in initial clinical research, is assumed for these strategies. Cox’s proportional hazard model is used with modern statistical approaches. In this paper, detailed modeling strategies for clinical risk prediction are proposed and demonstrated by using a case study on the cardiovascular disease. Experiments were conducted by employing Stepwise selection and Elastic Net with bootstrapping. Results give some insights for risk prediction and modeling with limitation of clinical data.

Keywords: Clinical risk prediction; Cox’s proportional hazard model; Bootstrapping; Variable selection; Stepwise selection; Elastic net (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-33-4359-7_2

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DOI: 10.1007/978-981-33-4359-7_2

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