Skip to content Skip to navigation
University of Warwick
  • Study
  • |
  • Research
  • |
  • Business
  • |
  • Alumni
  • |
  • News
  • |
  • About

University of Warwick
Publications service & WRAP

Highlight your research

  • WRAP
    • Home
    • Search WRAP
    • Browse by Warwick Author
    • Browse WRAP by Year
    • Browse WRAP by Subject
    • Browse WRAP by Department
    • Browse WRAP by Funder
    • Browse Theses by Department
  • Publications Service
    • Home
    • Search Publications Service
    • Browse by Warwick Author
    • Browse Publications service by Year
    • Browse Publications service by Subject
    • Browse Publications service by Department
    • Browse Publications service by Funder
  • Help & Advice
University of Warwick

The Library

  • Login
  • Admin

Theory and applications of delayed censoring models in survival analysis

Tools
- Tools
+ Tools

Heydari, Fariborz (1997) Theory and applications of delayed censoring models in survival analysis. PhD thesis, University of Warwick.

[img]
Preview
PDF
WRAP_Thesis_Heydari_1997.pdf - Requires a PDF viewer.

Download (15Mb) | Preview
Official URL: http://webcat.warwick.ac.uk/record=b1403966~S1

Request Changes to record.

Abstract

The objective of this thesis is to develop new statistical models for the analysis of censored survival data, particularly for the study of recidivism data, such as the reoffence data used in the analysis here. This has been an area of great interest in criminology in recent years. There is a growing literature on survival analysis in criminology, where interest centres on the time from an offender's conviction, or release from prison, to the first reconviction or reimprisonment. In deciding whether to release a prisoner on parole, the Parole Board is provided with a statistical score which estimates the chance that the prisoner will reoffend within the period of time that he or she would otherwise be in prison. This score is based on a survival analysis of data on a sample of releases from long-term prison sentences. To capture most reoffences which occur within 2 years of release, follow-up must continue for at least 3 years to allow for the delay between offence and conviction. We reanalyse the data by using a model which explicitly allows for this delay. We refer to this as 'delayed censoring model'. The new analysis can be applied to data with a substantially shorter length of follow-up. This means that risk scores can be constructed from more up-to-date data and at less cost.

It is models of this kind that we shall be concerned with in this thesis, and this is the principal motivation of the work done. The statistical models that this thesis provides bring in a number of new ideas which are undoubtedly useful both at a theoretical level and in applications.
Other major divisions of the work include:
(i) Assessing the possibility of an association between the delay and reoffence times by studying truncated distributions fitted to these data, by parametric, semi-parametric and nonparametric models. With the nonparametric approach we have developed a 'backward regression model' which is similar to the Cox model.
(ii) We have also discussed delayed censoring modification to the Cox model, and developed a more general semi-parametric model for all the data including both observed and censored cases. In this model the delay and reoffence times are allowed to be correlated. We refer to this as the 'generalized weighted hazards model'.
(iii) Finally, we have compared the results by applying all these models to the data. Although the parametric models give a good fit to the data, the semi-parametric and nonparametric models give a slightly better fit, as expected

Item Type: Thesis or Dissertation (PhD)
Subjects: H Social Sciences > HA Statistics
Library of Congress Subject Headings (LCSH): Failure time data analysis, Criminals -- Rehabilitation, Mathematical statistics, Recidivism -- Statistics -- Methodology, Probation, Prisoners, Criminal psychology
Official Date: 1997
Dates:
DateEvent
1997Submitted
Institution: University of Warwick
Theses Department: Department of Statistics
Thesis Type: PhD
Publication Status: Unpublished
Supervisor(s)/Advisor: Copas, John B.
Sponsors: Ministry of Science, Research and Technology (Iran) , Shiraz University
Extent: 243 leaves
Language: eng

Request changes or add full text files to a record

Repository staff actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics

twitter

Email us: wrap@warwick.ac.uk
Contact Details
About Us