Inference in semi-parametric spline mixed models for longitudinal data

被引:2
|
作者
Sinha S.K. [1 ]
Sattar A. [2 ]
机构
[1] School of Mathematics and Statistics, Carleton University, Ottawa, K1S 5B6, ON
[2] Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH
基金
加拿大自然科学与工程研究理事会;
关键词
Longitudinal response; Mixed model; Parametric bootstrap; Robust estimation; Spline regression;
D O I
10.1007/s40300-015-0059-2
中图分类号
学科分类号
摘要
In this paper, the authors investigate a robust semi-parametric mixed effects model for analyzing longitudinal data with an unspecified mean response function. The robust method, developed in the framework of the maximum likelihood, is used to bound the influence of potential outliers when estimating the model parameters. The authors also present a robust test procedure for assessing the significance of a variance component in the mixed model. An application is provided using a clinical dataset from a retinopathy of prematurity study in which longitudinal measurements were obtained from premature infants treated with supplemental oxygen. The empirical properties of the proposed estimators are also studied in simulations. © 2015 Sapienza Università di Roma.
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页码:377 / 395
页数:18
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