Literature DB >> 12179572

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

G Ghilagaber.   

Abstract

"The purpose of the paper is to compare results of estimation and inference concerning covariate effects as obtained from two approaches to the analysis of survival data with multiple causes of failure. The first approach involves a dynamic model for the cause-specific hazard rate. The second is based on a static logistic regression model for the conditional probability of having had an event of interest. The influence of sociodemographic characteristics on the rate of family initiation and, more importantly, on the choice between marriage and cohabitation as a first union, is examined. We found that results, generally, are similar across the methods considered. Some issues in relation to censoring mechanisms and independence among causes of failure are discussed." excerpt

Keywords:  Family And Household; Family Characteristics; Marriage; Marriage Patterns; Models, Theoretical; Nuptiality; Research Methodology; World

Mesh:

Year:  1998        PMID: 12179572     DOI: 10.1023/a:1004312403022

Source DB:  PubMed          Journal:  Qual Quant        ISSN: 0033-5177


  12 in total

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Journal:  Biometrics       Date:  1988-03       Impact factor: 2.571

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Journal:  J Math Biol       Date:  1986       Impact factor: 2.259

6.  The analysis of failure times in the presence of competing risks.

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Journal:  Biometrics       Date:  1978-12       Impact factor: 2.571

7.  Additive and multiplicative models for relative survival rates.

Authors:  J D Buckley
Journal:  Biometrics       Date:  1984-03       Impact factor: 2.571

8.  Covariate analysis of competing-risks data with log-linear models.

Authors:  M G Larson
Journal:  Biometrics       Date:  1984-06       Impact factor: 2.571

9.  Additive, multiplicative, and other models for disease risks.

Authors:  S D Walter; T R Holford
Journal:  Am J Epidemiol       Date:  1978-11       Impact factor: 4.897

10.  The analysis of rates and of survivorship using log-linear models.

Authors:  T R Holford
Journal:  Biometrics       Date:  1980-06       Impact factor: 2.571

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