IISER Kolkata ePrints Repository

Optimal Crossover Design for Generalized Linear Model with Binary Response

Jankar, Jeevan (2019) Optimal Crossover Design for Generalized Linear Model with Binary Response. Masters thesis, Indian Institute of Science Education and Research Kolkata.

[img] PDF (MS dissertation of JEEVAN JANKAR (14MS060)) - Submitted Version
Restricted to Repository staff only

Download (964Kb)


    In this thesis, we identify locally optimal crossover designs for generalized linear models. Generalized linear models are widely used for modeling the responses that are binary in nature. Pharmaceutical industries frequently conduct clinical trials where the outcome is either success or failure of a particular therapy. In this thesis, generalized linear models are used for such crossover experiments with binary responses. We use generalized estimating equations to estimate the model parameters along with their variances. Different correlation structures have been proposed to capture real situations.We identify optimal allocation of patients for different sequences of treatments. For two-treatment crossover designs, it has been shown via simulations that the optimal allocations are reasonably robust to the choices of the correlation structures. We discuss a real example of a multiple treatment crossover experiment using Latin square designs. A simulation study was presented to show that the optimization technique developed here is more efficient when responses from the same subject are more correlated.

    Item Type: Thesis (Masters)
    Additional Information: Supervisor: Abhyuday Mandal (Department of Statistics, University of Georgia); Co-Supervisor: Dr. Saugata Bandyopadhyay
    Uncontrolled Keywords: Crossover Design; Generalized Linear Models; Multiple-treatment Crossover Trails; Two-treatment Crossover Trails
    Subjects: Q Science > QA Mathematics
    Divisions: Department of Mathematics and Statistics
    Depositing User: IISER Kolkata Librarian
    Date Deposited: 14 Oct 2019 12:05
    Last Modified: 14 Oct 2019 12:05
    URI: http://eprints.iiserkol.ac.in/id/eprint/875

    Actions (login required)

    View Item