A latent changepoint model using a generalized estimating equations approach

被引：0

作者：

Lee, JH ^{[1
]}

Qaqish, BF

机构：

[1] Univ S Florida, H Lee Moffitt Canc Ctr, Tampa, FL 33612 USA

[2] Univ S Florida, Res Inst, Tampa, FL 33612 USA

[3] Univ N Carolina, Dept Biostat, Chapel Hill, NC USA

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2005年 / 34卷 / 05期

关键词：

a latent changepoint model; biomarkers; GEE; longitudinal data;

D O I：

10.1081/STA-200056815

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

We propose a latent changepoint model for the analysis of longitudinal biomarker data in relation to progression or recurrence of disease. A parametric model that contains a random changepoint in the expected biomarker values is considered. In this article, estimation through generalized estimating equations is proposed. The procedure allows estimation of the biomarker trend over time and the changepoint distribution. We provide the details of the estimation procedure. Through a Monte Carlo simulation study, several aspects of the small sample performance of the estimates are investigated.

引用

页码：1233 / 1242

页数：10

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