Literature DB >> 10851840

Alternative time scales and failure time models.

T Duchesne1, J Lawless.   

Abstract

In many reliability applications, there may not be a unique plausible scale in which to measure time to failure or assess performance. This is especially the case when several measures of usage are available on each unit. For example, the age, the total number of flight hours, and the number of landings are usage measures that are often considered important in aircraft reliability. Similarly, in medical or biological applications of survival analysis there are often alternative scales (e.g., Oakes, 1995). This paper considers the definition of a "good" time scale, along with methods of determining a time scale.

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Year:  2000        PMID: 10851840     DOI: 10.1023/a:1009616111968

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


  5 in total

1.  Semiparametric inference methods for general time scale models.

Authors:  Thierry Duchesne; Jerry Lawless
Journal:  Lifetime Data Anal       Date:  2002-09       Impact factor: 1.588

2.  Multiple time scales and the lifetime coefficient of variation: engineering applications.

Authors:  K B Kordonsky; I Gertsbakh
Journal:  Lifetime Data Anal       Date:  1997       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.  Marker processes in survival analysis.

Authors:  N P Jewell; J D Kalbfleisch
Journal:  Lifetime Data Anal       Date:  1996       Impact factor: 1.588

5.  Methods for the estimation of failure distributions and rates from automobile warranty data.

Authors:  J Lawless; J Hu; J Cao
Journal:  Lifetime Data Anal       Date:  1995       Impact factor: 1.588

  5 in total
  11 in total

1.  Semiparametric inference methods for general time scale models.

Authors:  Thierry Duchesne; Jerry Lawless
Journal:  Lifetime Data Anal       Date:  2002-09       Impact factor: 1.588

2.  Use of alternative time scales in Cox proportional hazard models: implications for time-varying environmental exposures.

Authors:  Beth Ann Griffin; Garnet L Anderson; Regina A Shih; Eric A Whitsel
Journal:  Stat Med       Date:  2012-04-25       Impact factor: 2.373

3.  Measuring agreement of multivariate discrete survival times using a modified weighted kappa coefficient.

Authors:  Ying Guo; Amita K Manatunga
Journal:  Biometrics       Date:  2008-05-23       Impact factor: 2.571

4.  Proportional hazards and threshold regression: their theoretical and practical connections.

Authors:  Mei-Ling Ting Lee; G A Whitmore
Journal:  Lifetime Data Anal       Date:  2009-12-04       Impact factor: 1.588

5.  Models and estimation for systems with recurrent events and usage processes.

Authors:  Jerald F Lawless; Martin J Crowder
Journal:  Lifetime Data Anal       Date:  2010-03-11       Impact factor: 1.588

6.  Threshold regression for survival data with time-varying covariates.

Authors:  Mei-Ling Ting Lee; G A Whitmore; Bernard A Rosner
Journal:  Stat Med       Date:  2010-03-30       Impact factor: 2.373

7.  Midlife cardiovascular health and 20-year cognitive decline: Atherosclerosis Risk in Communities Study results.

Authors:  Hector M González; Wassim Tarraf; Kimystian Harrison; B Gwen Windham; Jonathan Tingle; Alvaro Alonso; Michael Griswold; Gerardo Heiss; David Knopman; Thomas H Mosley
Journal:  Alzheimers Dement       Date:  2017-12-18       Impact factor: 21.566

8.  A case-control study relating railroad worker mortality to diesel exhaust exposure using a threshold regression model.

Authors:  Mei-Ling Ting Lee; G A Whitmore; Francine Laden; Jaime E Hart; Eric Garshick
Journal:  J Stat Plan Inference       Date:  2009       Impact factor: 1.111

9.  A reference relative time-scale as an alternative to chronological age for cohorts with long follow-up.

Authors:  Margaret Anne Hurley
Journal:  Emerg Themes Epidemiol       Date:  2015-12-18

10.  Survival analysis and classification methods for forest fire size.

Authors:  Pier-Olivier Tremblay; Thierry Duchesne; Steven G Cumming
Journal:  PLoS One       Date:  2018-01-10       Impact factor: 3.240

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