Grant Morgan, Ph.D.

Associate Dean for Research

Dr. Grant B. Morgan is professor in the Quantitative Methods graduate program in the Department of Educational Psychology (EDP) at Baylor School of Education, and he is also the associate dean for research and outreach in the School of Education and coordinator of the Quantitative Methods specialization graduate programs (M.A. & Ph.D.). He earned a Ph.D. in educational research and measurement from the University of South Carolina and joined the Baylor University faculty in 2012.

Morgan’s primary areas of research interest are latent variable models, psychometrics, classification, and nonparametric statistics. Related to these, he has parallel lines of research that involve (1) methodological investigations of advanced models using Monte Carlo methods and (2) applications of advanced quantitative modeling in a variety of areas via interdisciplinary collaboration. Morgan has authored well over 100 articles, manuscripts, book chapters, proceedings, and technical reports, and one book to date. His methodological works have been published in such journals as Structural Equation Modeling, Psychological Methods, Computational Statistics & Data Analysis, Methodology, and Language Assessment Quarterly. His interdisciplinary collaborations have appeared in such journals as The American Statistician, Journal of Applied Measurement, Psychological Assessment, Journal of Healthcare Management, and Women’s Health Issues. Over the past 20 years, Morgan has worked on over $20 million in externally funded research.

Morgan has numerous awards and nominations, including three distinguished paper awards from AERA-affiliated organizations, Cornelia Marschall Smith Professor of the Year nomination, and Division D Early Career Award nomination. Morgan is member of AERA’s Division D, Structural Equation Modeling, Multilevel Modeling, and Rasch special interest groups. Morgan previously served as a board member and treasurer of a regional AERA-affiliated organization and is currently serving as board member of another regional AERA-affiliated organization. He regularly serves as a panelist for the National Science Foundation and U.S. Department of Education . He is on the editorial board of the Journal of Psychoeducational Assessment and has reviewed manuscripts for Structural Equation Modeling, Psychometrika, Methodology, Multivariate Behavioral Research, and other top-tier methodological journals.

Degrees

Ph.D. Educational Research & Measurement
2012 | University of South Carolina, Columbia

M.S. Human Resources Management (Organization Performance track)
2005 | Western Carolina University, Cullowhee

B.S. Psychology
2003 | Clemson University

Research Interests

• Classification
  Classification, generally, refers to the process of simplifying data by grouping observations that have similarities together. There are many applications of classification in educational and psychological research, and there are many ways to perform classification. My research in this area focuses on the latent variable, or model-based, approach to classification.
• Psychometrics
  Psychometrics generally refers to the measurement of psychological phenomena and involves the application of advanced statistical techniques to psychological instruments. My research in this area focuses on providing validity evidence of existing instruments and exploring applications of existing psychometric ideas and models to new measurement scenarios. Ultimately, my research in psychometrics focuses on reaching correct conclusions about the existence and nature of psychological phenomena of interest.
• Latent Variable Models
  Latent variable models involve the examination of one or more theorized but directly unobservable variables, such as ability, intelligence, or achievement. A latent variable cannot itself be directly measured, but instruments may be developed that allow one to observe the manifestation of the latent variable. Models that include one or more latent variables require complex mathematical computation to allow researchers to make decisions from the manifestations of the latent variable. My research in this area is related to the accurate estimation of relationships between latent and observed variables.

Expertise

• Psychometrics
• Psychological Assessment
• Assessment (Testing) in Education
• Structural Equation Modeling
• Quantitative Methods

 Select Publications

• Psychological Methods | May 1, 2024
  “Regularizing threshold priors with sparse response patterns in Bayesian factor analysis with categorical indicators”
  with co-authors Dr. R. Noah Padgett, Harvard University, and Tim Lomas, Harvard University
• Structural Equation Modeling, Vol. 27, Issue 6, p. 974-974 | 2020.
  “Generating nonnormal distributions via Gaussian mixture models”
• Book “Survey Scales: A Guide to Development, Analysis, and Reporting” | 2016
  with co-author(s) Dr. Robert L. Johnson, University of South Carolina
• Structural Equation Modeling, Vol. 22, p. 76-86 | 2015
  “Mixed Mode Latent Class Analysis: An Examination of Fit Index Performance for Classification”
• Structural Equation Modeling, Vol. 21, Issue 3, p. 424-438 | 2014
  “A Comparison of Diagonal Weighted Least Squares Robust Estimation Techniques for Ordinal Data”
  with co-author(s) Dr. Christine DiStefano, University of South Carolina.

Professional Leadership

Structural Equation Modeling SIG Chair, AERA | 2018-2021

Courses

• Nonparametric Statistics (EDP 5V95)
• Philosophy and Practice of Science in Education Research (EDP 5V95)
• Psychometric Theory (EDP 6337)
• Measurement & Evaluation (EDP 5340)
• Applied Multiple Regression/Correlation Analysis (EDP 6362)
• Experimental Design I (EDP 6360)
• Item Response Theory (EDP 6366)
• Latent Variable Models in Education (EDP 6365)