2021 Early Career Award
Date & Time: Wednesday, July 21 at 12:30pm EST
Conventional item response data analysis typically relies on several assumptions, such as local item independence, respondent independence, and homogeneity. However, these assumptions are often violated in practice and difficult to verify. To weaken the reliance on these assumptions, I propose a new perspective on item response data – to view them as network data representing relationships between two types of actors, respondents, and items. In this network view on item response data, a tie between the two types of actors is made when a correct response is given to the item by the respondent. The probability of a tie between a respondent and an item is then modeled as a function of a person attribute, an item attribute, and a distance between the person and the item in a low-dimensional Euclidean space. In this latent space item response model, the probability of a tie is determined not only by the person’s and the item’ attributes but also by how closely or distantly the person is located from the item in latent space. I will explain how the conventional assumptions of local item independence, respondent independence, and homogeneity are relaxed in the proposed latent space item response model. Additional benefits of the proposed network perspective on item response data and the proposed modeling approach are discussed with empirical data examples.
About the Speaker
Minjeong Jeon is an Associate Professor of Advanced Quantitative Methods at the UCLA department of Education. Prior to coming to UCLA, she was an Assistant Professor of Quantitative Psychology at the Ohio State University. She obtained her Ph.D in Quantitative Methods and MA in Statistics from UC Berkeley in 2012. Her research revolves around developing, applying, and estimating latent variable models for studying measurement and growth. Her recent research topics include understanding individual differences in item response and decision making processes. Dr. Jeon is an (co)author of four software packages and has published over 55 papers in methodology and substantive peer-review journals. She is a winner of NCME dissertation award and a recipient of three early career awards given by NCME, AERA, and APA. Dr. Jeon currently serves as an Associate Editor for Psychometrika and Journal of Educational and Behavioral Statistics.