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SELECTING THE COVARIANCE STRUCTURE IN MIXED MODEL USING STATISTICAL METHODS CALIBRATION | Science Publications

机译:使用统计方法校准在混合模型中选择协方差结构|科学出版物

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> In this article the analysis of experiment of repeated measures design is considered which is used often in different fields of studies. In order to analyze the experiment of repeated measures design efficiently we need to select the suitable covariance structure which required a lot of efforts. In the current paper an approach is used to guide the selection of the covariance structure for the analysis of repeated measures design with high rate of success. Five well known model selection criteria are used in the approach. Simulation study is used to evaluate the approach in terms of its ability to select the right covariance structure. The evaluation of the approach was in terms of its percentage of times that it identifies the right covariance structure. Overall, the simulation study showed excellent performance for the approach in all the study cases. The main result of our article is that we recommend considering the approach as a standard way to select the right covariance structure.
机译: >本文考虑重复测量设计的实验分析,该实验经常用于不同的研究领域。为了有效地分析重复测量设计的实验,我们需要选择合适的协方差结构,这需要大量的努力。在当前的论文中,一种方法被用来指导协方差结构的选择,以分析具有高成功率的重复测量设计。该方法使用了五个众所周知的模型选择标准。仿真研究用于根据选择正确协方差结构的能力来评估该方法。该方法的评估依据是它确定正确的协方差结构的次数百分比。总体而言,模拟研究表明在所有研究案例中该方法均具有出色的性能。本文的主要结果是,我们建议将这种方法视为选择正确的协方差结构的标准方法。

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