Improving variance function estimation in semiparametric longitudinal data analysis

被引：3
|
作者：
Leng, Chenlei [1 ]
Tang, Cheng Yong [1 ]
机构：
[1] Natl Univ Singapore, Dept Stat & Appl Probabil, Singapore 117546, Singapore
来源：
CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE | 2011年 / 39卷 / 04期
关键词：
Asymptotic relative efficiency; local linear estimator; longitudinal data analysis; variance function estimation; MSC 2010: Primary 62G08; secondary; 62G05; REGRESSION; MODELS;
D O I：
10.1002/cjs.10129
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 an efficient and robust method for variance function estimation in semiparametric longitudinal data analysis. The method utilizes a local log-linear approximation for the variance function and adopts a generalized estimating equation approach to account for within subject correlations. We show theoretically and empirically that our method outperforms estimators using working independence that ignores the correlations. The Canadian Journal of Statistics 39: 656670; 2011. (c) 2011 Statistical Society of Canada
引用
收藏
页码：656 / 670
页数：15
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