Delwin Carter

Delwin Carter is a quantitative research methodologist specializing in mixture modeling, longitudinal latent variable analysis, psychometrics, simulation methods, and reproducible research. His work focuses on the development, evaluation, and application of quantitative methods for studying heterogeneity and change in complex behavioral, psychological, and educational data. Across this work, he examines how analytic decisions influence statistical inference, measurement quality, and the substantive conclusions researchers draw from complex models.

His methodological research has a particular emphasis on latent class analysis, latent profile analysis, latent transition analysis, and random-intercept latent transition analysis. Using Monte Carlo simulation, methodological reviews, and applied studies, his work evaluates model performance, measurement and design decisions, post-estimation inference, and reporting practices. A central goal of this research is to translate complex methodological problems into practical guidance and reproducible tools for applied researchers.

Delwin earned his Ph.D. in Education from the University of California, Santa Barbara, with emphases in Quantitative Methods and College Teaching. His dissertation examined the performance of random-intercept latent transition analysis using a large-scale Monte Carlo simulation study.

He teaches research methods and quantitative analysis in psychology at California State University, Northridge. His teaching emphasizes methodological reasoning, model interpretation, and reproducible research practices, helping students move beyond the mechanical use of statistical software toward a deeper understanding of statistical inference and research design. 

He also founded and directs The MIX Institute, a quantitative research and training initiative focused on mixture modeling, longitudinal and latent variable methods, collaborative methodological research, and the development of emerging researchers.