Bio

Grant B. Morgan, Ph.D., is Associate Professor in the Quantitative Methods graduate program in the Department of Educational Psychology (EDP) at Baylor School of education, and he is also the 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 transdisciplinary collaboration. Morgan has authored over 70 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, Computational Statistics & Data Analysis, Methodology, and Language Assessment Quarterly. His transdisciplinary collaborations have appeared in such journals as Journal of Applied Measurement, Psychological Assessment, Journal of Healthcare Management, and Women’s Health Issues.

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 has served as a reviewer for NSF’s Directorate for Education & Human Resources and Directorate for Social, Behavioral, & Economic Sciences. He is on the editorial board of the Journal of Psychoeducational Assessment and has reviewed manuscripts for Structural Equation Modeling, Methodology, Multivariate Behavioral Research, and other top-tier methodological journals.

Degrees (3)

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

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

B.S. - Psychology
2003
Clemson University
Clemson, SC

Research Interests (3)

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 (4)

Psychological Assessment

Assessment (Testing) in Education

Structural Equation Modeling

Quantitative Methods

Select Publications (9) Showing 5 of 9. Showing 9 of 9. Show All Show Less

Survey Scales: A Guide to Development, Analysis, and Reporting (2016), Johnson & Morgan

Dr. Grant B. Morgan, associate professor, published "Survey Scales: A Guide to Development, Analysis, and Reporting", August 1, 2016, with co-author(s) Dr. Robert L. Johnson, University of South Carolina.

Temporal Attitudes Profile Transition among Adolescents: A longitudinal Examination using Mover- stayer Latent Transition Analysis (in press)

Dr. Grant B. Morgan, associate professor, published "Temporal Attitudes Profile Transition among Adolescents: A longitudinal Examination using Mover- stayer Latent Transition Analysis" in Psychological Assessment, with co-author(s) Kevin E. Wells, doctoral candidate, James Andretta, Superior Court of the District of Columbia, and Michael McKay, University of Liverpool.

Examining Differences in Method Effects Related to Negative Wording: An Example Using Rasch Mixture Modeling (in press)

Dr. Grant B. Morgan, associate professor, published "Examining Differences in Method Effects Related to Negative Wording: An Example Using Rasch Mixture Modeling" in Journal of Applied Measurement, October 19, 2016, with co-author(s) Dr. Christine DiStefano, University of South Carolina, and Robert Motl, University of Illinois Urbana-Champaign.

Latent Profile Analysis with nonnormal Mixtures: A Monte Carlo Examination of Model Selection Accuracy (2016)

Dr. Grant B. Morgan, associate professor, published "Latent Profile Analysis with nonnormal Mixtures: A Monte Carlo Examination of Model Selection Accuracy" in Computational Statistics & Data Analysis, Vol. 93, p. 146-161, January 1, 2016, with co-author(s) Dr. Kari J. Hodge, NACE International, and Aaron R. Baggett, University of Mary Hardin-Baylor.

Are Fit Indices Biased in Favor of Bi-factor Models in Cognitive Ability research?: A Comparison of Fit in Correlated Factors, Higher-order, and Bi-factor models via Monte Carlo Simulations (2015)

Dr. Grant B. Morgan, associate professor, published "Are Fit Indices Biased in Favor of Bi-factor Models in Cognitive Ability research?: A Comparison of Fit in Correlated Factors, Higher-order, and Bi-factor models via Monte Carlo Simulations" in Journal of Intelligence, Vol. 3, p. 2-20, July 1, 2015, with co-author(s) Dr. Kari J. Hodge, NACE International, Kevin E. Wells, doctoral candidate, and Dr. Marley W. Watkins, non-resident scholar.

An Investigation of Growth Mixture Models for Studying the Flynn Effect (2014)

Dr. Grant B. Morgan, associate professor, published "An Investigation of Growth Mixture Models for Studying the Flynn Effect" in Journal of Intelligence, Vol. 2, p. 156-179, October 1, 2014, with co-author(s) Dr. Alex Beaujean, associate professor.

Mixed Mode Latent Class Analysis: An Examination of Fit Index Performance for Classification (2015)

Dr. Grant B. Morgan, associate professor, published "Mixed Mode Latent Class Analysis: An Examination of Fit Index Performance for Classification" in Structural Equation Modeling, Vol. 22, p. 76-86, January 10, 2015.

Interrater Reliability Indices commonly Used in Scoring Student Essays: A Monte Carlo Investigation of Index Accuracy (2014)

Dr. Grant B. Morgan, associate professor, published "Interrater Reliability Indices commonly Used in Scoring Student Essays: A Monte Carlo Investigation of Index Accuracy" in Language Assessment Quarterly, Vol. 11, Issue 3, p. 302-324, September 1, 2014, with co-author(s) Dr. Min Zhu, Dr. Robert L. Johnson, University of South Carolina, and Dr. Kari J. Hodge, NACE International.

A Comparison of Diagonal Weighted Least Squares Robust Estimation Techniques for Ordinal Data (2014)

Dr. Grant B. Morgan, associate professor, published "A Comparison of Diagonal Weighted Least Squares Robust Estimation Techniques for Ordinal Data" in Structural Equation Modeling, Vol. 21, Issue 3, p. 424-438, October 28, 2014, with co-author(s) Dr. Christine DiStefano, University of South Carolina.