Workshop on Statistical Methodology and Applications to Biomedicine and Finance

Yuan-chin Ivan Chang, Academia Sinica Assessing the Predictive Power of Newly Added Biomarkers As medical research and technology advance, there are always new biomarkers found and predictive models proposed for improving the diagnostic performance of diseases. Therefore, in addition to the existing biomarkers and predictive models, how to assess new biomarkers becomes an important research problem. Many classification performance measures, which are usually based on the performance on the whole cut-off values, were applied directly to this type of problems. However, in a medical diagnosis, some cut-off points are more important, such as those points within the range of high specificity. Thus, as the partial area under the ROC curve to the area under ROC curve, we study the partial integrated discriminant improvement (pIDI) for evaluating the predictive ability of a newly added marker at a pre-specified range of cut-offs. Theoretical property of estimate of the proposed measure is reported. The performance of this new measure is then compared with that of the partial area under an ROC curve. The numerical results use synthesized are presented, and a liver cancer dataset is used for demonstration purposes. (This is a co-work with Professor Zhanfeng Wang at University of Science Technology of China) Hong Chen, Shanghai Jiaotong University Default and Credit Risk Evaluation and Pricing Big Data Approach In this talk, I will present the motivation, initiative and preliminary results on the credit risk research I have been working on with my colleagues at SAIF. Jie Chen, Novartis Pharmaceuticals Sequential Testing of Disproportionality of Two Poisson Processes with Applications to Drug Safety? Two sequences of independent, possibly non-homogeneous, Poisson counting processes are investigated sequentially to detect an increasing or decreasing trend of proportion for one process relative to another over a period of time. The problem is formulated as sequential testing of a null hypothesis of some types of odds ratios (OR). Conditional on both margins (subtotals of both processes in the subintervals and the sequential cumulative totals for each process), the random variables of events in the subintervals for one Poisson process follow a non-central multivariate hypergeometric distributions. Then the sequential testing of the null hypothesis is performed using sequential generalized likelihood ratio (sequential GLR) tests where explicit formulas are further developed and computational implementation is provided. The proposed methods are illustrated with an example in vaccine safety surveillance where an increasing reporting proportion of a rare adverse event is of interest.