报告人：蔡敬衡
报告题目：Statistical Analysis of Transformation Latent Variable Models with
Multivariate Censored Data
报告时间：2014年10月22日周三下午3:40
报告地点：江苏师范大学数学与统计学院学术报告厅（静远楼1506室）
报告内容摘要：
Transformation latent variable models are proposed in this study to analyze multivariate censored data. The proposed models generalize conventional linear transformation models to semiparametric transformation models that accommodate latent variables. The characteristics of the latent variables were assessed based on several correlated observed indicators through measurement equations. A Bayesian approach was developed with Bayesian Psplines technique and the Markov chain Monte Carlo algorithm to estimate the unknown parameters and transformation functions. Simulation shows that the performance of the proposed methodology is satisfactory. The proposed method was applied to analyze a cardiovascular disease data set
蔡敬衡简介：
2008年于香港中文大学统计系获博士学位，2013年任中山大学副教授，现任中山大学统计系副主任。研究领域包括结构方程模型的分析及应用，贝叶斯分析，统计计算等，在Structural Equation Modeling: A Multidisciplinary Journal，Statistics in Medicine，Psychometrika等SCI期刊发表文章十余篇，并译著《结构方程模型: 贝叶斯方法》。