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Sequential Analysis with Applications to Clinical Trials

  • Author / Creator
    Samuylova, Evgenia
  • The topic of the thesis is an overview of some sequential and change-point detection methods with applications to clinical trials. Performing sequential monitoring is important for ethical, economical and other reasons. It is important to terminate a study as soon as possible when potentially harmful treatments are used or when financial resources are limited. The modern theory of sequential testing of hypotheses started with works of Wald and Barnard on quality control of military supplies during World War II. Since then sequential methods received a lot of attention. In this thesis we consider application of truncated sequential methods to four different models. First, we consider sequential testing of composite hypotheses in the presence of nuisance parameters. Second, we describe sequential procedures for binary data with risk-adjustment. Then, we consider non-parametric methods for sequential monitoring of longitudinal data. We finish the thesis with an example of monitoring proportions in the context of waiting time at emergency departments in hospitals.

  • Subjects / Keywords
  • Graduation date
    2012-06
  • Type of Item
    Thesis
  • Degree
    Master of Science
  • DOI
    https://doi.org/10.7939/R36997
  • 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)
    • Gombay, Edit (Math & Stat Sciences)
  • Examining committee members and their departments
    • Dinu, Irina (Public Health Sciences)
    • Prasad, Narasimha (Math & Stat Sciences)