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pmid: 15831575
We study a hybrid model that combines Cox proportional hazards regression with tree-structured modeling. The main idea is to use step functions, provided by a tree structure, to 'augment' Cox (1972) proportional hazards models. The proposed model not only provides a natural assessment of the adequacy of the Cox proportional hazards model but also improves its model fitting without loss of interpretability. Both simulations and an empirical example are provided to illustrate the use of the proposed method.
Male, Biometry, Censored data models, STRUCTURED SURVIVAL ANALYSIS, Statistics & Probability, CORONARY HEART-DISEASE, survival, censored survival times, WESTERN, California, Applications of statistics to biology and medical sciences; meta analysis, FOLLOW-UP EXPERIENCE, REGRESSION, BIC, Humans, Prospective Studies, Censored survival times, Proportional Hazards Models, Models, Statistical, Western Collaborative Group Study, MORTALITY, RESIDUALS, trees, Middle Aged, Cox proportional hazards models, Survival Analysis, Survival trees, Time series, auto-correlation, regression, etc. in statistics (GARCH), Cardiovascular Diseases, COLLABORATIVE GROUP, TESTS, Mathematical & Computational Biology, Monte Carlo Method, GOODNESS, cardiovascular epidemiology
Male, Biometry, Censored data models, STRUCTURED SURVIVAL ANALYSIS, Statistics & Probability, CORONARY HEART-DISEASE, survival, censored survival times, WESTERN, California, Applications of statistics to biology and medical sciences; meta analysis, FOLLOW-UP EXPERIENCE, REGRESSION, BIC, Humans, Prospective Studies, Censored survival times, Proportional Hazards Models, Models, Statistical, Western Collaborative Group Study, MORTALITY, RESIDUALS, trees, Middle Aged, Cox proportional hazards models, Survival Analysis, Survival trees, Time series, auto-correlation, regression, etc. in statistics (GARCH), Cardiovascular Diseases, COLLABORATIVE GROUP, TESTS, Mathematical & Computational Biology, Monte Carlo Method, GOODNESS, cardiovascular epidemiology
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popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |