Southwest Jiaotong University School of Mathematics


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“创源”大讲堂: Joint modeling of longitudinal continuous, binary and ordinal events

ag网站亚游登录:   作者:郑海涛     日期:2015-05-30 00:00:00   点击数:  




讲座题目:Joint modeling of longitudinal continuous, binary and ordinal events



报告内容:In medical studies, repeated measurements of continuous, binary and ordinal outcomes are routinely collected from the same patient. Instead of modelling each outcome separately, in this study we propose to jointly model the trivariate longitudinal responses, so as to take account of the inherent association between the different outcomes and thus improve statistical inferences. This work is motivated by a large cohort study in the North West of England, involving trivariate responses from each patient: Body Mass Index, Depression (Yes/No) ascertained with cut-off score not less than 8 at the Hospital Anxiety and Depression Scale, and Pain Interference generated from the Medical Outcomes Study 36-item short-form health survey with values returned on an ordinal scale 1-5. There are some well-established methods for combined continuous and binary, or even continuous and ordinal responses, but little work was done on the joint analysis of continuous, binary and ordinal responses. We propose conditional joint random effects models, which take into account the inherent association between the continuous, binary and ordinal outcomes. Bayesian analysis methods are used to make statistical inferences. Simulation studies show that, by jointly modelling the trivariate outcomes, standard deviations of the estimates of parameters in the models are smaller and much more stable, leading to more efficient parameter estimates and reliable statistical inferences. In the real data analysis, the proposed joint analysis yields a much smaller deviance information criterion value than the separate analysis, and shows other good statistical properties too.


潘建新,英国曼彻斯特大学(University of Manchester)ag网站亚游登录终身教授,2009年至2012年任曼彻斯特大学ag网站亚游登录统计系系主任。他是英国皇家统计学会(The Royal Statistical Society)Fellow,国际统计研究院(The International Statistical Institute)Elected Member. 目前担任统计学杂志《Biometrics》的Associated Editor。主要从事统计学领域内复杂数据模型的理论研究及其在生物医学、经济金融及工业上的应用研究,取得了多项创新性研究成果。这些成果发表在包括美国统计学会杂志(Journal of the American Statistical Association) 和英国生物计量学杂志(Biometrika)在内的多个世界一流统计学期刊上。至今已发表70多篇学术论文,出版学术专著2部(Springer出版社和科学出版社)。





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