Practicum: The C-S method in computation of the logistic normal integral

Zhao, Yi (2014) Practicum: The C-S method in computation of the logistic normal integral. Masters thesis, Memorial University of Newfoundland.

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In logistic regression models with measurement error involved, the likelihood func- tion is often taking the form as the logistic normal integral. Among several methods that have been proposed to compute this kind of integral, the method by E. Crouch and D. Spiegelman (1990) (C-S), programmed in FORTRAN, is believed to be a good candidate from the computational perspective. We investigate this method by calling the FORTRAN code into R, and compare its performance with the classic Gaussian Quadrature method. The simulation results show that the C-S approach is much faster than the classic Gaussian Quadrature algorithm without losing any precision of the estimates, especially when the sample size is large.

Item Type: Thesis (Masters)
Item ID: 6382
Additional Information: Includes bibliographical references (pages 38-40).
Department(s): Science, Faculty of > Mathematics and Statistics
Date: May 2014
Date Type: Submission
Library of Congress Subject Heading: Logistic regression analysis; Definite integrals; Numerical integration

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