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Maximum likelihood estimation in the proportional hazards cure model.
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- Author(s): Lu, Wenbin1
- Source:
Annals of the Institute of Statistical Mathematics. Sep2008, Vol. 60 Issue 3, p545-574. 30p.- Subject Terms:
- Source:
- Additional Information
- Abstract: The proportional hazards cure model generalizes Cox’s proportional hazards model which allows that a proportion of study subjects may never experience the event of interest. Here nonparametric maximum likelihood approach is proposed to estimating the cumulative hazard and the regression parameters. The asymptotic properties of the resulting estimators are established using the modern empirical process theory. And the estimators for the regression parameters are shown to be semiparametric efficient. [ABSTRACT FROM AUTHOR]
- Abstract: Copyright of Annals of the Institute of Statistical Mathematics is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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