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On estimation of covariate-specific residual time quantiles under the proportional hazards model.
Crouch, Luis Alexander; May, Susanne; Chen, Ying Qing.
Afiliación
  • Crouch LA; Department of Biostatistics, University of Washington, Seattle, WA, 98105, USA. crouch@uw.edu.
  • May S; Department of Biostatistics, University of Washington, Seattle, WA, 98105, USA.
  • Chen YQ; Program in Biostatistics and Biomathematics, Fred Hutchinson Cancer Research Center, Seattle, WA, 98109, USA.
Lifetime Data Anal ; 22(2): 299-319, 2016 Apr.
Article en En | MEDLINE | ID: mdl-26058825
ABSTRACT
Estimation and inference in time-to-event analysis typically focus on hazard functions and their ratios under the Cox proportional hazards model. These hazard functions, while popular in the statistical literature, are not always easily or intuitively communicated in clinical practice, such as in the settings of patient counseling or resource planning. Expressing and comparing quantiles of event times may allow for easier understanding. In this article we focus on residual time, i.e., the remaining time-to-event at an arbitrary time t given that the event has yet to occur by t. In particular, we develop estimation and inference procedures for covariate-specific quantiles of the residual time under the Cox model. Our methods and theory are assessed by simulations, and demonstrated in analysis of two real data sets.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Modelos de Riesgos Proporcionales Tipo de estudio: Clinical_trials / Diagnostic_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans / Infant / Newborn / Pregnancy Idioma: En Revista: Lifetime Data Anal Año: 2016 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Modelos de Riesgos Proporcionales Tipo de estudio: Clinical_trials / Diagnostic_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans / Infant / Newborn / Pregnancy Idioma: En Revista: Lifetime Data Anal Año: 2016 Tipo del documento: Article País de afiliación: Estados Unidos