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报告题目:

Joint modeling of multivariate longitudinal data with latent variables

邀 请 人: 孙六全 研究员
报 告 人: Prof.Xin-Yuan Song,Department of Statistics, Chinese University of Hong Kong, Hong Kong
时间地点: 2014年5月26日上午10:00 N205
报告摘要:

This research considers a joint modeling approach to investigate the dynamic patterns and possible heterogeneity of the associations and interrelationships among variables of interest in multivariate longitudinal data analysis. The model consists of a conditional latent variable model and a mixed hidden transition model to simultaneously address different types of dependencies within the data. The maximum likelihood procedure, coupled with the expectation-maximization algorithm and efficient sampling schemes, is developed to conduct parameter estimation. The issues of model selection and hypothesis testing are also addressed. The empirical performance of the proposed methodology is examined via simulation studies. A real data example is reported for illustration.

报告人简介:

 

学术报告中国科学院数学与系统科学研究院应用数学研究所
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