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Investigation of covariance structures in modelling longitudinal ordinal responses with skew normal random effect

机译:抗纵序偏斜正常随机效应调查协方差结构

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In this article, a mixed ordinal responses is presented with fundamental skew normal random effects and a link function based on fundamental skew normal is used due to the greater flexibility. An appropriate random effect variance covariance (VC) structure is determined to obtain reliable statistical inferences. Therefore, various types of random effects VC structures are considered. We use simulation to find parameters estimates properties and the model is applied for analyzing the Schizophrenia Collaborative Study data. Our results show that AR(1) VC structure improves parameters estimates substantially and the drugs effect significantly on the schizophrenia treatment over time.
机译:在本文中,混合序数响应具有基本偏斜的正常随机效应,并且由于具有更大的灵活性,使用基于基本偏斜正常的链路功能。确定适当的随机效应方差协方差(VC)结构获得可靠的统计推论。因此,考虑各种类型的随机效应VC结构。我们使用模拟来查找参数估计属性,并且应用模型用于分析精神分裂症协作研究数据。我们的研究结果表明,AR(1)VC结构大幅提高了参数估计,药物随着时间的推移而显着影响精神分裂症治疗。

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