Assistant Professor of Quantitative Methods, Measurement, and Statistics
Psychometrics; Measurement Theory; Item Response Theory; Test Design and Analysis; Diagnostic Classification Models
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 practices. 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 complex latent traits more accurately and provide insightful and actionable feedback to stakeholders. His pioneering research won him the 2017 Distinguished Paper Award by the American Educational Research Association (AERA), the 2018 New Investigator Award by AERA, and the 2022 Rising Star Designation by the Association for Psychological Science (APS). 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, self-injury, and criminal justice, as well as special populations such as LGBTQ+ groups, patients with ADHD, and children with altruism. Dr. Liu is the Statistical Editor of the International Journal of Behavioral Medicine (the Official Journal of the International Society of Behavioral Medicine). He is also the co-chair 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.