The Annals of Statistics

Asymptotic results for maximum likelihood estimators in joint analysis of repeated measurements and survival time

Donglin Zeng and Jianwen Cai

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Abstract

Maximum likelihood estimation has been extensively used in the joint analysis of repeated measurements and survival time. However, there is a lack of theoretical justification of the asymptotic properties for the maximum likelihood estimators. This paper intends to fill this gap. Specifically, we prove the consistency of the maximum likelihood estimators and derive their asymptotic distributions. The maximum likelihood estimators are shown to be semiparametrically efficient.

Article information

Source
Ann. Statist., Volume 33, Number 5 (2005), 2132-2163.

Dates
First available in Project Euclid: 25 November 2005

Permanent link to this document
https://projecteuclid.org/euclid.aos/1132936559

Digital Object Identifier
doi:10.1214/009053605000000480

Mathematical Reviews number (MathSciNet)
MR2211082

Zentralblatt MATH identifier
1086.62034

Subjects
Primary: 62G07: Density estimation
Secondary: 62F12: Asymptotic properties of estimators

Keywords
Maximum likelihood estimation profile likelihood asymptotic distribution longitudinal data survival time

Citation

Zeng, Donglin; Cai, Jianwen. Asymptotic results for maximum likelihood estimators in joint analysis of repeated measurements and survival time. Ann. Statist. 33 (2005), no. 5, 2132--2163. doi:10.1214/009053605000000480. https://projecteuclid.org/euclid.aos/1132936559


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