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A quantile regression model for failure-time data with time-dependent covariates.
Gorfine, Malka; Goldberg, Yair; Ritov, Ya'acov.
Afiliação
  • Gorfine M; Department of Statistics and Operation Research, Tel Aviv University, Ramat Aviv, 6997801 Tel Aviv, Israel gorfinem@post.tau.ac.il.
  • Goldberg Y; Department of Statistics, University of Haifa, Mount Carmel, 31905 Haifa, Israel.
  • Ritov Y; Department of Statistics, The Hebrew University of Jerusalem, Mount Scopus, 91905 Jerusalem, Israel and Department of Statistics, University of Michigan, Ann Arbor, MI 48194, USA.
Biostatistics ; 18(1): 132-146, 2017 01.
Article em En | MEDLINE | ID: mdl-27485534
Since survival data occur over time, often important covariates that we wish to consider also change over time. Such covariates are referred as time-dependent covariates. Quantile regression offers flexible modeling of survival data by allowing the covariates to vary with quantiles. This article provides a novel quantile regression model accommodating time-dependent covariates, for analyzing survival data subject to right censoring. Our simple estimation technique assumes the existence of instrumental variables. In addition, we present a doubly-robust estimator in the sense of Robins and Rotnitzky (1992, Recovery of information and adjustment for dependent censoring using surrogate markers. In: Jewell, N. P., Dietz, K. and Farewell, V. T. (editors), AIDS Epidemiology. Boston: Birkhaäuser, pp. 297-331.). The asymptotic properties of the estimators are rigorously studied. Finite-sample properties are demonstrated by a simulation study. The utility of the proposed methodology is demonstrated using the Stanford heart transplant dataset.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Análise de Sobrevida / Análise de Regressão / Modelos Estatísticos Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Biostatistics Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Israel

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Análise de Sobrevida / Análise de Regressão / Modelos Estatísticos Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Biostatistics Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Israel