Research, Evaluation, Measurement, and Statistics Program
About the Program
The College of Education: Research, Evaluation, Measurement, & Statistics (REMS) PhD program is designed to prepare students for successful careers at leading educational institutions. Its goal is to provide training and experiences that enable graduates to become highly productive researchers and excellent educators. The program affords students opportunities to work closely with faculty on research projects and to develop their own research programs. The diverse expertise of the REMS faculty provides a research and learning environment that supports a wide range of interests.
The Research, Evaluation, Measurement, & Statistics (REMS) PhD program is a concentration area within the Department of Educational Psychology & Leadership at Texas Tech University. The program is guided by the standards of the American Psychological Association (APA), the American Educational Research Association (AERA), and sound professional judgment of experienced and caring faculty.
The REMS PhD program is designed to foster strong theoretical foundations and expertise in quantitative methodology and statistical techniques. Students are trained as critical thinkers that are capable of working independently and collaboratively on teams, to design/conduct empirical research; enhance measurement, apply cutting-edge statistical methods, develop/disseminate new techniques; and evaluate programs that influence policy.
Visit the College of Education webpage for more information about other programs offered by the college.
If you're interested in enrolling in the REMS program, visit our application webpage.
TODD D. LITTLE (PhD, University of California Riverside). Professor of Educational Psychology & Leadership; founding Director of the Texas Tech Institute for Measurement, Methodology, Analysis and Policy (IMMAP); 65th President of the APA's Division 5: Evaluation, Measurement, and Statistics; Fellow of the AAAS, APA, and APS; Founder of the Stats Camps (statscamp.org). Dr. Little's recent research focuses on longitudinal structural equation modeling, planned missing data design, retrospective pre-post design, and visual analog scale.
JAEHOON LEE (PhD, University of Kansas). Assistant Professor of Educational Psychology & Leadership; Program Coordinator of the REMS PhD program; Co-Director of IMMAP. Dr. Lee's research interests are primarily on the development, evaluation, and application of latent variable modeling, multilevel modeling, mixture modeling, item response theory, propensity score analysis, Bayesian structural equation modeling, complex survey data analysis, and power analysis.
KWANGHEE JUNG (PhD, McGill University). Assistant Professor of Educational Psychology & Leadership; Research Associate of IMMAP. Dr. Jung's research focuses on the development, evaluation, and application of latent variable modeling, multilevel modeling, latent growth curve modeling, time series analysis, generalized structured component analysis, constrained principal component analysis, and brain imaging data analysis.
The REMS faculty share an appointment with IMMAP. For more information, please visit IMMAP Directors and Researchers.