ROBUST ESTIMATION IN PARTIAL LINEAR MIXED MODEL FOR LONGITUDINAL DATA

被引：0

作者：

秦国友

朱仲义

机构：

[1] Department of Statistics East China Normal University

[2] Department of Statistics Fudan University Shanghai 200062

[3] China Department of Biostatistics

[4] School of Public Health

[5] Shanghai 200032

[6] Shanghai 200433

来源：

Acta Mathematica Scientia | 2008年 / 02期

关键词：

Generalized estimating equation; longitudinal data; metropolis algorithm; mixed effect; partial linear model; robustness;

D O I：

暂无

中图分类号：

TP11 [自动化系统理论];

学科分类号：

摘要：

In this article,robust generalized estimating equation for the analysis of par- tial linear mixed model for longitudinal data is used.The authors approximate the non- parametric function by a regression spline.Under some regular conditions,the asymptotic properties of the estimators are obtained.To avoid the computation of high-dimensional integral,a robust Monte Carlo Newton-Raphson algorithm is used.Some simulations are carried out to study the performance of the proposed robust estimators.In addition, the authors also study the robustness and the efficiency of the proposed estimators by simulation.Finally,two real longitudinal data sets are analyzed.

引用

页码：333 / 347

页数：15

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