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Tree-structured subgroup analysis for censored survival data: Validation of computationally inexpensive model selection criteria |
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| Authors: | |
| Institution: | (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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