Graham Rifenbark

Postdoctoral Research Associate

Expertise: Research Methods, Measurement, and Evaluation

Educational Psychology


About Me

I earned my Ph.D. in Educational Psychology from the Research Methods, Measurement, and Evaluation (RMME) program at the University of Connecticut (UCONN) in May 2019.

Currently, I am a Postdoctoral Research Associate in the Department of Educational Psychology housed in the Neag School of Education at UCONN. I am the methodologist on an Institute of Educational Sciences (IES) Measurement project to develop and validate the College and Career Readiness for Transition (CCR4T) instrument.

Prior to my current position, I’ve conducted research over the past 7 years, in chronological order, at the Center for Research Methods and Data Analysis (CRMDA) at the University of Kansas (KU); the University of Connecticut (UConn) as a Graduate Research Assistant (GRA); and at the Kansas University Center on Developmental Disabilities (KUCDD) at KU as a postdoctoral researcher.

Methodological Research Interests

Broadly speaking, I am interested in latent variable modeling, the estimation of these models, and the ways in which their fit to data are assessed. I also have great interest in researching how latent variable models can be used to validate instruments and test their functioning across diverse groups and other cultures. To that end, I conduct Monte Carlo simulation studies to determine Type I error rates and power (or sensitivity) of methodological approaches that are commonly utilized.

For my dissertation, I executed Monte Carlo simulation studies that concerned the utility and sensitivity of structural measures of fit that have recently been proposed in the context of multiple group models. First, I examined the impact model size (e.g., number of indicators per factor), measurement quality (e.g., standardized factor loadings), and group sample sizes had on Type I error rates. In a subsequent simulation, I introduced structural misspecifications (of varying levels of severity) to the mean structure, covariance structure, and mean and covariance structures simultaneously by generating population differences between groups to determine the statistical power (i.e., sensitivity) of these structural measures of fit.

Applied Research Interests

With respect to applied research, I have co-authored numerous manuscripts in the field of Special Education with a large focus on transition from adolescence to adulthood. Specifically, I have published validation studies of measures on College and Career Readiness, School Climate, and Self-Determination. Additionally, I have evaluated interventions in the context of both randomized experiments and quasi-experimental designs.

Graham Rifenbark.
Contact Information
Emailgraham.rifenbark@uconn.edu
CV Rifenbark CV
Office LocationGentry 119A