学术报告
报告人： 涂冬生教授
Queen's University, Canada
报告时间：6月11日（周三）下午2：30
报告地点：数学楼第三报告厅
摘 要： Identification and assessment of biomarkers which can be used to predict the response of a patient to a specific treatment is a very active research area of health sciences. The significance of the biomarker is usually assessed by a test of interaction between the biomarker and treatment. Many biomarkers are measured on a continuous scale but in clinical practise, it is preferred patients can be classified into two categories such as biomarker positive and negative based on a cutpoint. In this talk, I will present a Bayesian approach my colleagues and I developed recently which can provide statistical inference simultaneously on the cupoint and biomarker-treatment interaction.
欢迎师生参加！
统计研究院
2014年6月9日