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Tree-structured subgroup analysis for censored survival data: Validation of computationally inexpensive model selection criteria
Authors:Abdissa?Negassa  author-information"  >  author-information__contact u-icon-before"  >  mailto:anegassa@aecom.yu.edu"   title="  anegassa@aecom.yu.edu"   itemprop="  email"   data-track="  click"   data-track-action="  Email author"   data-track-label="  "  >Email author,Antonio?Ciampi,Michal?Abrahamowicz,Stanley?Shapiro,Jean-Fran?ois?Boivin
Affiliation:(1) Department of Epidemiology and Population Health, Albert Einstein College of Medicine of Yeshiva University, Bronx, NY, USA;(2) Department of Epidemiology and Biostatistics, McGill University, Montreal, Canada;(3) Clinical Epidemiology, Montreal General Hospital, Montreal, Canada;(4) Center for Clinical Epidemiology and Community studies, The Sir Mortimer B. Davis Jewish General Hospital, Montreal, Canada
Abstract:The performance of computationally inexpensive model selection criteria in the context of tree-structured subgroup analysis is investigated. It is shown through simulation that no single model selection criterion exhibits a uniformly superior performance over a wide range of scenarios. Therefore, a two-stage approach for model selection is proposed and shown to perform satisfactorily. Applied example of subgroup analysis is presented. Problems associated with tree-structured subgroup analysis are discussed and practical solutions are suggested.
Keywords:censored survival data  regression tree  model selection  two-stage approach  subgroup analysis
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