Delwin Carter, Ph. D.
Quantitative Methodologist
Mixture modeling • longitudinal analysis • simulation studies • reproducible research
Research Focus
Mixture Modeling
Latent class, profile, and transition models for studying heterogeneity in psychological and developmental data.
Simulation Studies
Monte Carlo simulations evaluating statistical performance of longitudinal mixture models.
Reproducible Research
Transparent computational workflows integrating statistical modeling, simulation, and reproducible reporting.
About
Delwin Carter, Ph.D.
I am a quantitative methodologist whose research focuses on mixture modeling, longitudinal analysis, and simulation-based evaluation of statistical methods. My work examines how complex data structures can be modeled in ways that better capture heterogeneity, developmental change, and measurement uncertainty.
My path into quantitative methodology was not linear. Early challenges with statistics shifted through mentorship and guided research experience, ultimately leading to a sustained focus on methodological rigor and analytic clarity. Today my work centers on mixture and longitudinal modeling, where I use simulation studies and latent variable techniques to evaluate statistical performance and improve the application of advanced models in developmental and educational research.
Figure 1. Monte Carlo simulation results examining bias and coverage in random intercept latent transition analysis models across varying sample sizes and parameter conditions.
Research
Current Research
My current research examines the statistical performance of longitudinal mixture models through large-scale Monte Carlo simulation. In particular, I study random intercept latent transition analysis (RI-LTA) to understand how model specification, sample size, and measurement conditions influence estimation accuracy and classification quality.
These studies use automated Mplus workflows and high-performance computing environments to simulate thousands of model conditions. The goal is to clarify when complex mixture models perform reliably and to provide practical guidance for researchers applying these methods in developmental and educational research.
Teaching
Teaching & Research Training
My teaching focuses on helping researchers develop a strong conceptual and practical understanding of quantitative methodology. I teach graduate-level courses in research methods and statistics, emphasizing the connections between statistical theory, model interpretation, and applied research practice.
In these courses, students learn to design rigorous studies, evaluate statistical assumptions, and apply advanced modeling techniques to real research questions. My goal is to help researchers move beyond mechanical use of statistical software and develop the methodological reasoning necessary to conduct transparent and reproducible research.
Institute
The MIX Institute
The MIX Institute is a research and training initiative focused on quantitative methods, mixture modeling, and collaborative research.
The Institute provides structured opportunities for students to participate in literature synthesis projects, secondary data research, and quantitative methods workshops while contributing to ongoing research projects.
Publications
Selected Publications
Lawrie, I. L., Carter, D., Nylund-Gibson, K., & Kim, H. S. Frontiers in Psychology, 2025
Nylund-Gibson, K., Garber, A. C., Carter, D. B., Chan, M., Arch, D. A., Simon, O., Whaling, K., Tartt, E., & Lawrie, S. I. Psychological Methods, 2023
Moore, S. A., Carter, D., Kim, E. K., Furlong, M. J., Nylund-Gibson, K., & Dowdy, E. School Mental Health, 2024