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题名: Inference of Nested Variance Components in a Longitudinal Myopia Intervention Trial
作者: Hsiao, Chuhsing Kate;Tsai, Miao-Yu;Chen, Ho-Min
贡献者: 統計資訊研究所
关键词: Correlation;Nested repeated measurements;REML;Schwarz criterion
日期: 2005-11
上传时间: 2012-10-25T09:03:01Z
出版者: John Wiley & Sons, Ltd.
摘要: This paper was motivated by a double-blind randomized clinical trial of myopia intervention. In addition
to the primary goal of comparing treatment e ects, we are concerned with the modelling of correlation
that may come from two possible sources, one among the longitudinal observations and the other between
measurements taken from both eyes per subject. The data are nested repeated measurements. We
suggest three models for analysis. Each one expresses the correlation di erently in various covariance
structures. We articulate their di erences and describe the implementations in estimation using commercial
statistical software. The computer output can be further utilized to perform model selection with
Schwarz criterion. Simulation studies are conducted to evaluate the performance under each model. Data
of the myopia intervention trial are reanalysed with these models for illustration. The results indicate
that atropine is more e ective in reducing the progression rate, the rates are homogeneous across subjects,
and, among the suggested models, the one with independent random e ects of two eyes ts best.
We conclude that model selection is a crucial step before making inference with estimates; otherwise
the correlation may be attributed incorrectly to a di erent mechanism. The same conclusion applies to
other variance components as well.
關聯: Statistics in Medicine, 24: 3251-3267
显示于类别:[統計資訊研究所] 期刊論文

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