Literature DB >> 23832309

An introduction to survival models: in honor of Ross Prentice.

David Oakes1.   

Abstract

I review some key ideas and models in survival analysis with emphasis on modeling the effects of covariates on survival times. I focus on the proportional hazards model of Cox (J R Stat Soc B 34:187-220, 1972), its extensions and alternatives, including the accelerated life model. I briefly describe some models for competing risks data, multiple and repeated event-time data and multivariate survival data.

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Year:  2013        PMID: 23832309     DOI: 10.1007/s10985-013-9276-2

Source DB:  PubMed          Journal:  Lifetime Data Anal        ISSN: 1380-7870            Impact factor:   1.588


  4 in total

1.  Time for a smoke? One cigarette reduces your life by 11 minutes.

Authors:  M Shaw; R Mitchell; D Dorling
Journal:  BMJ       Date:  2000-01-01

Review 2.  Applying competing risks regression models: an overview.

Authors:  Bernhard Haller; Georg Schmidt; Kurt Ulm
Journal:  Lifetime Data Anal       Date:  2012-09-26       Impact factor: 1.588

3.  Multiple time scales in survival analysis.

Authors:  D Oakes
Journal:  Lifetime Data Anal       Date:  1995       Impact factor: 1.588

4.  Regression on quantile residual life.

Authors:  Sin-Ho Jung; Jong-Hyeon Jeong; Hanna Bandos
Journal:  Biometrics       Date:  2009-12       Impact factor: 2.571

  4 in total
  1 in total

1.  This special issue contains several papers on clinical trials, exemplifying Ross Prentice's influence. Preface.

Authors:  Jianwen Cai; Li Hsu
Journal:  Lifetime Data Anal       Date:  2013-10-16       Impact factor: 1.588

  1 in total

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