Acta mathematica scientia,Series B

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ROBUST ESTIMATION IN PARTIAL LINEAR MIXED MODEL FOR LONGITUDINAL DATA

Qin Guoyou; Zhu Zhongyi   

  1. Department of Statistics, East China Normal University, Shanghai 200062, China
    Department of Biostatistics, School of Public Health, Fudan University, Shanghai 200032, China
  • Received:2006-01-12 Revised:2006-06-05 Online:2008-04-20 Published:2008-04-20
  • Contact: Zhu Zhongyi

Abstract:

In this article, robust generalized estimating equation for the analysis of partial linear mixed model for longitudinal data is used. The authors approximate the nonparametric 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.

Key words: Generalized estimating equation, longitudinal data, metropolis
algorithm,
mixed effect, partial linear model, robustness

CLC Number: 

  • 62F35
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