- Ph.D., Quantitative Psychology, University of North Carolina
- B.S., Psychology, James Madison University
- M.A., Psychological Sciences, James Madison University
The Pennsylvania State University
State College, PA 16801
Edna Bennett Pierce Prevention Research Center
My graduate training focused on assessing model fit of structural equation models, factor analysis models, latent growth curve models, and item response theory models. My postdoctoral training focused on latent class analysis models, generalized linear mixed effects models, and missing data analysis. My current research focuses on causal inferences for mediation processes, which is funded by a NIDA R03 grant.
Maydeu-Olivares, A., Kramp, U., Garcia-Forero, C., Coffman, D. L., & Gallardo-Pujol, D. (in press). The effect of varying the number of response alternatives in rating scales: Experimental evidence from intra-individual effects. Behavior Research Methods.
Coffman, D. L., & BeLue, R. (in press). Using item response theory to detect differential item functioning in health disparities research. Journal of Community Psychology.
Coffman, D. L. (2008). Model misspecification in covariance structure models: Some implications for power and Type I error. Methodology, 4(4), 159-167.
Coffman, D. L., Maydeu-Olivares, A., & Arnau, J. (2008). Asymptotically distribution-free interval estimation for an intraclass correlation coefficient with applications to longitudinal data. Methodology, 4(1), 4-9.
Coffman, D. L., Patrick, M. E., Palen, L., Rhoades, B. L., & Ventura, A. K. (2007). Why do high school seniors drink? Implications for a targeted approach to intervention. Prevention Science, 8, 241-248.
Maydeu-Olivares, A., Coffman, D. L., & Hartmann, W. M. (2007). Asymptotically distribution-free interval estimation for coefficient alpha. Psychological Methods, 12(2), 157-176.
Maydeu-Olivares, A., & Coffman, D. L. (2006). Random intercept item factor analysis. Psychological Methods, 11(4), 344-362.
Coffman, D. L., & Millsap, R. E. (2006). Evaluating latent growth curve models using individual fit statistics.Structural Equation Modeling, 13(1), 1-27.
Preacher, K. J., & Coffman, D. L. (2006, May). Computing Power and Minimum Sample Size for RMSEA [Computer Software]. Available from http://www.quantpsy.org