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包含测量误差协变量的广义部分线性混合效应模型

GENERALIZED PARTIALLY LINEAR MIXED-EFFECTS MODELS INCORPORATING MISMEASURED COVARIATES.

作者信息

Liang Hua

机构信息

Department of Biostatistics and Computational Biology, University of Rochester, Rochester, NY 14642, USA.

出版信息

Ann Inst Stat Math. 2009 Mar 1;61(1):27-46. doi: 10.1007/s10463-007-0146-0.

Abstract

In this article we consider a semiparametric generalized mixed-effects model, and propose combining local linear regression, and penalized quasilikelihood and local quasilikelihood techniques to estimate both population and individual parameters and nonparametric curves. The proposed estimators take into account the local correlation structure of the longitudinal data. We establish normality for the estimators of the parameter and asymptotic expansion for the estimators of the nonparametric part. For practical implementation, we propose an appropriate algorithm. We also consider the measurement error problem in covariates in our model, and suggest a strategy for adjusting the effects of measurement errors. We apply the proposed models and methods to study the relation between virologic and immunologic responses in AIDS clinical trials, in which virologic response is classified into binary variables. A dataset from an AIDS clinical study is analyzed.

摘要

在本文中,我们考虑一个半参数广义混合效应模型,并提出结合局部线性回归、惩罚拟似然和局部拟似然技术来估计总体参数和个体参数以及非参数曲线。所提出的估计器考虑了纵向数据的局部相关结构。我们建立了参数估计器的正态性以及非参数部分估计器的渐近展开。为了实际应用,我们提出了一种合适的算法。我们还在模型中考虑了协变量中的测量误差问题,并提出了一种调整测量误差影响的策略。我们将所提出的模型和方法应用于研究艾滋病临床试验中的病毒学和免疫学反应之间的关系,其中病毒学反应被分类为二元变量。分析了一个艾滋病临床研究的数据集。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c7f9/2768363/2b61666f92b6/nihms78899f1.jpg

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