Literature DB >> 3358994

How dependent causes of death can make risk factors appear protective.

E Slud1, D Byar.   

Abstract

It is shown, using the results of Slud and Rubinstein (1983, Biometrika 70, 643-649) in a specially constructed theoretical example, that competing latent failure times Ti and Ci and a two-level covariate Vi, if analyzed as though Ti and Ci are independent for each Vi level, can lead to exactly the wrong conclusion about the ordering of Pr(Ti greater than or equal to t[Vi = 1) and Pr(Ti greater than or equal to t[Vi = 0) for every t. This phenomenon can never be excluded on purely statistical grounds using such data and should be considered when interpreting data analyses involving competing risks.

Mesh:

Year:  1988        PMID: 3358994

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  7 in total

1.  Analysis of survival data with multiple causes of failure: a comparison of hazard- and logistic-regression models with application in demography.

Authors:  G Ghilagaber
Journal:  Qual Quant       Date:  1998-08

2.  The use and interpretation of competing risks regression models.

Authors:  James J Dignam; Qiang Zhang; Masha Kocherginsky
Journal:  Clin Cancer Res       Date:  2012-01-26       Impact factor: 12.531

3.  Score tests for independence in semiparametric competing risks models.

Authors:  Mériem Saïd; Nadia Ghazzali; Louis-Paul Rivest
Journal:  Lifetime Data Anal       Date:  2009-08-28       Impact factor: 1.588

4.  The protective impact of a covariate on competing failures with an example from a bone marrow transplantation study.

Authors:  C Di Serio
Journal:  Lifetime Data Anal       Date:  1997       Impact factor: 1.588

Review 5.  Statistical methods for dependent competing risks.

Authors:  M L Moeschberger; J P Klein
Journal:  Lifetime Data Anal       Date:  1995       Impact factor: 1.588

6.  Choice and interpretation of statistical tests used when competing risks are present.

Authors:  James J Dignam; Maria N Kocherginsky
Journal:  J Clin Oncol       Date:  2008-08-20       Impact factor: 44.544

7.  Total and cause-specific mortality in the cardiovascular health study.

Authors:  Anne B Newman; Michael C Sachs; Alice M Arnold; Linda P Fried; Richard Kronmal; Mary Cushman; Bruce M Psaty; Tamara B Harris; John A Robbins; Gregory L Burke; Lewis H Kuller; Thomas Lumley
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2009-09-01       Impact factor: 6.053

  7 in total

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