University of SaskatchewanHARVEST
  • Login
  • Submit Your Work
  • About
    • About HARVEST
    • Guidelines
    • Browse
      • All of HARVEST
      • Communities & Collections
      • By Issue Date
      • Authors
      • Titles
      • Subjects
      • This Collection
      • By Issue Date
      • Authors
      • Titles
      • Subjects
    • My Account
      • Login
      JavaScript is disabled for your browser. Some features of this site may not work without it.
      View Item 
      • HARVEST
      • Electronic Theses and Dissertations
      • Graduate Theses and Dissertations
      • View Item
      • HARVEST
      • Electronic Theses and Dissertations
      • Graduate Theses and Dissertations
      • View Item

      Applicability of multiplicative and additive hazards regression models in survival analysis

      Thumbnail
      View/Open
      SabujSarker_Thesis_040811.pdf (1.315Mb)
      Date
      2011-04
      Author
      Sarker, Sabuj
      Type
      Thesis
      Degree Level
      Masters
      Metadata
      Show full item record
      Abstract
      Background: Survival analysis is sometimes called “time-to-event analysis”. The Cox model is used widely in survival analysis, where the covariates act multiplicatively on unknown baseline hazards. However, the Cox model requires the proportionality assumption, which limits its applications. The additive hazards model has been used as an alternative to the Cox model, where the covariates act additively on unknown baseline hazards. Objectives and methods: In this thesis, performance of the Cox multiplicative hazards model and the additive hazards model have been demonstrated and applied to the transfer, lifting and repositioning (TLR) injury prevention study. The TLR injury prevention study was a retrospective, pre-post intervention study that utilized a non-randomized control group. There were 1,467 healthcare workers from six hospitals in Saskatchewan, Canada who were injured from January 1, 1999 to December 1, 2006. De-identified data sets were received from the Saskatoon Health Region and Regina Qu’appelle Health Region. Time to repeated TLR injury was considered as the outcome variable. The models’ goodness of fit was also assessed. Results: Of a total of 1,467 individuals, 149 (56.7%) in the control group and 114 (43.3%) in the intervention group had repeated injuries during the study period. Nurses and nursing aides had the highest repeated TLR injuries (84.8%) among occupations. Back, neck and shoulders were the most common body parts injured (74.9%). These covariates were significant in both Cox multiplicative and additive hazards models. The intervention group had 27% fewer repeated injuries than the control group in the multiplicative hazards model (HR= 0.63; 95% CI=0.48-0.82; p-value=0.0002). In the additive model, the hazard difference between the intervention and the control groups was 0.002. Conclusion: Both multiplicative and additive hazards models showed similar results, indicating that the TLR injury prevention intervention was effective in reducing repeated injuries. The additive hazards model is not widely used, but the coefficient of the covariates is easy to interpret in an additive manner. The additive hazards model should be considered when the proportionality assumption of the Cox model is doubtful.
      Degree
      Master of Science (M.Sc.)
      Department
      Community Health and Epidemiology
      Program
      Community Health and Epidemiology
      Supervisor
      Lim, Hyun (June)
      Committee
      Pahwa, Punam; Janzen, Bonnie L.
      Copyright Date
      April 2011
      URI
      http://hdl.handle.net/10388/etd-04082011-154713
      Subject
      Additive hazards model
      Multiplicative Cox hazards model
      Repeated MSI Injuris
      Collections
      • Graduate Theses and Dissertations
      University of Saskatchewan

      University Library

      The University of Saskatchewan's main campus is situated on Treaty 6 Territory and the Homeland of the Métis.

      © University of Saskatchewan
      Contact Us | Disclaimer | Privacy