Uncovering the Hidden Complexity of Statistical Models Presented by Dr. Wes Bonifay, University of Missouri Friday, October 13 11:00 a.m. ET Virtual meeting – Webex meeting room Model complexity is the ability of a statistical model to fit a wide range of data patterns. Complexity is routinely assessed by simply counting the number of freely […]

Hidden Markov Models With An Unknown Number Of Hidden States Presented by Dr. Xinyuan Song, The Chinese University of Hong Kong Friday, NOVEMBER  3 10:00 a.m. ET Virtual meeting – Webex meeting room Hidden Markov models (HMMs) are valuable tools for analyzing longitudinal data due to their capability to describe dynamic heterogeneity. Conventional HMMs typically […]

“Applications of Artificial Intelligence and Natural Language Processing in Educational Measurement,” presented by Matthias von Davier, Boston College.

“Modeling Coarsened Categorical Variables: Techniques and Software, ” presented by Joseph Schafer, United States Census Bureau.

“Bookmaking for Binary Outcomes: Prediction, Profits, and the IMV”, presented by Ben Domingue, Stanford University.

“Testing an Elaborate Theory of a Causal Hypothesis”, presented by Dylan Small, University of Pennsylvania.

“Searching for Truth through Data”, presented by Dr. Edsel A. Pena, Professor of Statistics at the University of South Carolina.

“Experimental Evaluation of Algorithm-Assisted Human Decision-Making: Application to Pretrial Public Safety Assessment,” presented by Kosuke Imai, Professor of Government and of Statistics, Harvard University, Institute for Quantitative Social Science.

“Combining Experimental and Population Data to Estimate Population Treatment Effects,” presented by Dr. Elizabeth Stuart, Johns Hopkins Bloomberg School of Public Health

“Combining Experimental and Population Data to Estimate Population Treatment Effects,” presented by Dr. Elizabeth Stuart, Johns Hopkins Bloomberg School of Public Health