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Bias corrected maximum likelihood estimator under the Generalized Linear Model for a binary variable

Authors
Park, MingueChoi, Boseung
Issue Date
2008
Publisher
TAYLOR & FRANCIS INC
Keywords
bias; likelihood equation; log likelihood function
Citation
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, v.37, no.8, pp.1507 - 1514
Indexed
SCIE
SCOPUS
Journal Title
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
Volume
37
Number
8
Start Page
1507
End Page
1514
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/125493
DOI
10.1080/03610910802063772
ISSN
0361-0918
Abstract
Under the generalized linear models for a binary variable, an approximate bias of the maximum likelihood estimator of the coefficient, that is a special case of linear parameter in Cordeiro and McCullagh (1991), is derived without a calculation of the third-order derivative of the log likelihood function. Using the obtained approximate bias of the maximum likelihood estimator, a bias-corrected maximum likelihood estimator is defined. Through a simulation study, we show that the bias-corrected maximum likelihood estimator and its variance estimator have a better performance than the maximum likelihood estimator and its variance estimator.
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