Literature DB >> 27738350

Higher Dimensional Clayton-Oakes Models for Multivariate Failure Time Data.

R L Prentice1.   

Abstract

The Clayton-Oakes bivariate failure time model is extended to dimensions m > 2 in a manner that allows unspecified marginal survivor functions for all dimensions less than m. Special cases that allow unspecified marginal survivor functions of dimension q with q < m, while making some provisions for dependencies of dimension greater than q, are also described.

Entities:  

Keywords:  Bivariate survivor function; Clayton–Oakes model; Copula; Cross ratio; Multivariate survivor function

Year:  2015        PMID: 27738350      PMCID: PMC5059106          DOI: 10.1093/biomet/asv057

Source DB:  PubMed          Journal:  Biometrika        ISSN: 0006-3444            Impact factor:   2.445


  1 in total

1.  Covariance analysis of censored survival data.

Authors:  N Breslow
Journal:  Biometrics       Date:  1974-03       Impact factor: 2.571

  1 in total
  1 in total

1.  Nonparametric estimation of the multivariate survivor function: the multivariate Kaplan-Meier estimator.

Authors:  Ross L Prentice; Shanshan Zhao
Journal:  Lifetime Data Anal       Date:  2016-09-27       Impact factor: 1.588

  1 in total

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