Quasi-likelihood for Right-Censored Data in the Generalized Linear Model
Document Type
Article
Publication Date
6-4-2009
Publication Title
Communications in Statistics - Theory and Methods
DOI
10.1080/03610920802499504
ISSN
1532-415X
Abstract
This article proposes a method for estimation in a generalized linear model with right-censored data. Consider the model , μ i (β) = g(β T X i ), where v and g are known functions, e i , i = 1,…,n are identically and independently distributed with mean 0 and finite variance φ2, but the distribution is unspecified. We use Kaplan–Meier estimates to replace the censored observations and employ quasi-likelihood to estimate the parameters. Consistency and asymptotic normality of the parameter estimates are derived. The performance of the proposed method for small sample sizes is investigated by simulation study. The new method is illustrated with the Stanford heart transplant data.
Recommended Citation
Yu, Lili, Ruifeng Yu, Liang Liu.
2009.
"Quasi-likelihood for Right-Censored Data in the Generalized Linear Model."
Communications in Statistics - Theory and Methods, 38 (13): 2187-2200: Taylor & Francis Online.
doi: 10.1080/03610920802499504
https://digitalcommons.georgiasouthern.edu/bee-facpubs/175
Comments
Copyright belongs to Taylor and Francis Online
This pathway has an Open Access fee associated with it