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Generalised partial linear single-index mixed models for repeated measures data

机译:重复测量数据的广义局部线性单指标混合模型

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摘要

In this paper, we propose generalised partial linear single-index mixed models for analysing repeated measures data. A penalised quasi-likelihood approach using P-spline is used to estimate the nonparametric function, linear parameters, and single-index coefficients. Asymptotic properties of the estimators are developed when the dimension of spline basis grows with increasing sample size. Simulation examples and two applications: the study of health effects of air pollution in North Carolina, and treatment effect of naltrexone on health costs for alcohol-dependent individuals, illustrate the effectiveness of our approach.
机译:在本文中,我们提出了用于分析重复测量数据的广义局部线性单指标混合模型。使用P样条的惩罚拟似然法可用于估计非参数函数,线性参数和单索引系数。当样条基础的尺寸随着样本大小的增加而增长时,估计量的渐近性质得以发展。模拟示例和两个应用程序:对北卡罗莱纳州空气污染的健康影响的研究以及纳曲酮对酒精依赖者的健康费用的治疗作用,说明了我们方法的有效性。

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