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Multiple Time Scales and Longitudinal Measurements in Event History Analysis
Umeå University, Faculty of Social Sciences, Statistics.
2005 (English)Doctoral thesis, monograph (Other academic)
Abstract [en]

A general time-to-event data analysis known as event history analysis is considered. The focus is on the analysis of time-to-event data using Cox's regression model when the time to the event may be measured from different origins giving several observable time scales and when longitudinal measurements are involved. For the multiple time scales problem, procedures to choose a basic time scale in Cox's regression model are proposed. The connections between piecewise constant hazards, time-dependent covariates and time-dependent strata in the dual time scales are discussed. For the longitudinal measurements problem, four methods known in the literature together with two proposed methods are compared. All quantitative comparisons are performed by means of simulations. Applications to the analysis of infant mortality, morbidity, and growth are provided.

Place, publisher, year, edition, pages
Umeå: Statistik , 2005. , 130 p.
Series
Statistical studies, ISSN 1100-8989 ; 33
Keyword [en]
Statistics, Cox regression, multiple events, proportiona hazards, random effects, survival analysis, time-dependent covariates, time origin
Keyword [sv]
Statistik
National Category
Probability Theory and Statistics
Research subject
Statistics
Identifiers
URN: urn:nbn:se:umu:diva-420ISBN: 91-7305-812-2 (print)OAI: oai:DiVA.org:umu-420DiVA: diva2:143422
Public defence
2005-02-11
Available from: 2005-01-21 Created: 2005-01-21Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf