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An Examination of Spatial Scan Statistics for Time to Event Data

  • Author / Creator
    Usman, Iram
  • The spatial scan statistic (SSS) has been used for the identification of geographical clusters of higher than expected numbers of cases of a condition such as an illness. Disease outbreaks in a geographic area are a typical example. These statistics can also identify geographic areas with longer time to events if the SSS uses appropriate distribution. Other authors have proposed the exponential and Weibull distributions for the event times. We have established the log-Weibull distribution as a new and alternative approach for the SSS, and compared and contrasted the three distributions through simulation studies to investigate right censoring. Different datasets from the exponential, Weibull, log-Normal, and gamma probability distributions have been generated in order to test the robustness of the SSS's. Three differential censoring settings were imposed on the generated datasets to test the detection power of the true spatial cluster by each SSS. The method along with the existing exponential and Weibull SSS's were also illustrated on the time to specialist visit (cardiology or internal medicine) data for discharged patients presenting to an Emergency Department for atrial fibrillation and flutter in Alberta during 2010-2011.

  • Subjects / Keywords
  • Graduation date
    2016-06
  • Type of Item
    Thesis
  • Degree
    Master of Science
  • DOI
    https://doi.org/10.7939/R36D5PK2M
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
    English
  • Institution
    University of Alberta
  • Degree level
    Master's
  • Department
    • Department of Mathematical and Statistical Sciences
  • Specialization
    • Statistics
  • Supervisor / co-supervisor and their department(s)
    • Rosychuk, Rhonda (Department of Paediatrics)
    • Karunamuni, Rohana (Department of Statistics)
  • Examining committee members and their departments
    • Yuan, Yan (School of Public Health)
    • Heo, Giseon (School of Dentistry)