来源:统计学院

7月18日 | Guanyu Hu : Bayesian nonparametric methods for handling item and examinee heterogeneity in assessment data

来源:统计学院发布时间:2024-07-16浏览次数:10

时  间:2024年7月18日15:30 - 16:30

地  点:普陀校区理科大楼A1514

报告人:Guanyu Hu 得克萨斯大学休斯顿健康科学中心助理教授

主持人:谌自奇华东师范大学研究员

摘  要:

Item response theory (IRT) is a popular modeling paradigm for measuring subject latent traits and item properties according to discrete responses in tests or questionnaires. There are very limited discussions on heterogeneity pattern detection for both items and individuals. In this talk, we introduce two nonparametric Bayesian approaches for clustering items and individuals simultaneously We evaluate our model via a series of simulations and apply it to English assessment data. This data analysis example nicely illustrates how test makers can use our model to distinguish different types of students and aid in the design of future tests.

报告人简介:

Dr. Hu is the assistant professor at the University of Texas Health Science Center at Houston. Dr. Hu’s research mainly focuses on Bayesian nonparametric methods, spatial and spatio-temporal statistics, point process, and causal inference. Dr. Hu has also worked on the analysis of clinical trials, spatial transcriptomic, regional economics, environmental science, educational measurements, and sports data. Now, Dr. Hu is the associate editor of Biometrics, AoAS, Environmental and Ecological Statistics and Statistics and its interface and he also serves as the Chair of ASA statistics in sports section and the Program Chair of ISBA East Asia Chapter. Dr. Hu is elected member of ISI.