James L. Peugh, PhD

Quantitative Psychologist, Behavioral Medicine and Clinical Psychology

Academic Affiliations

Associate Professor, UC Department of Pediatrics

Phone 513-636-4336


Cross-sectional, longitudinal, and multilevel latent variable mixture modeling; missing data handling; pedagogical manuscripts

James Peugh, PhD, focuses his research on missing data handling and multilevel modeling techniques. He has published five manuscripts in those areas. As a post-doctoral fellow, Dr. Peugh received advanced training in dyadic data analysis, which resulted in three additional publications. As an assistant professor at the University of Virginia, his research focused on Monte Carlo testing of longitudinal and cross-sectional finite mixture modeling techniques.

Dr. Peugh's co-authored several publications with numerous colleagues that used a wide variety of categorical and continuous latent variable modeling techniques involving cross-sectional or longitudinally-sampled data. He also serves on the editorial board of the Journal of School Psychology and have reviewed over fifty manuscripts submitted for publication in several journals.

PhD: University of Nebraska, Lincoln, NE.

Fellowship: Department of Psychology, University of Nebraska. Lincoln, NE.

Feldon DF, Peugh J, Timmerman BE, Maher MA, Hurst M, Strickland D, Gilmore JA, Stiegelmeyer C. Graduate students’ teaching experiences improve their methodological research skills. Science. 2011.

Peugh JL, Fan X. Evaluating the performance of enumeration indices in multilevel growth mixture models: a Monte Carlo simulation. Structural Equation Modeling. 2011;11:1-19.

Peugh JL. A practical guide to multilevel modeling. J Sch Psychol. 2010 Feb;48(1):85-112.

Peugh JL, Fan X. Growth mixture modeling: concepts and implementation. Advances and Applications in Statistical Sciences. 2010.

Peugh JL, Enders CK. Missing data in educational research: a review of reporting practices and suggestions for improvement. Review of Educational Research. 2004;74:525-556.