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Understanding Behavior: From Neurons to Societies

Ren Liu

Professional Title: 
Assistant Professor of Quantitative Methods, Measurement, and Statistics
Office: 
SSM 306B
Research Interests: 

Psychometrics; Measurement Theory; Item Response Theory; Test Design and Analysis; Diagnostic Classification Models

Bio: 
Dr. Ren Liu is an Assistant Professor of Quantitative Methods, Measurement, and Statistics at the University of California, Merced. He earned his Ph.D. in Research and Evaluation Methodology with a specialization in Quantitative Methods at the University of Florida in 2018. Dr. Liu has centered his work on developing advanced statistical and measurement methods in behavioral and social sciences and translating innovative methods for applied researchers to promote best practice. These efforts have encompassed methodological research in advancing psychometric theories and their applications in test development and analysis. His work in psychometric methods contemplates ways to measure human complex latent traits more accurately and provide insightful and actionable feedback to stakeholders. All his methodological work has aimed to advance measurement theories and models across different types of data. His pioneering research won him the 2017 Distinguished Paper Award and the 2018 New Investigator Award, which were both conferred by the American Educational Research Association (AERA). In addition to his primary research in methodology, Dr. Liu also collaborates with several colleagues on substantive research projects. This substantive work covers a variety of domains including substance use and self-injury, as well as special populations such as children with altruism. Dr. Liu is a member of the National Council on Measurement in Education (NCME) Mission Fund Committee, and he is the author of the “Anatomy of Measurement”, an NCME Mission Fund YouTube Animation Project. Dr. Liu teaches both undergraduate and graduate level courses including Analysis of Psychological Data, Item Response Theory, and Measurement Theory and Psychometrics.