Bill received his A.B. degree in psychology from Stanford University and his Ph.D from the University of Oregon. He also completed a postdoctoral fellowship at Stanford University in personality psychology. Before joining the faculty at St. Johns in January, 2004, Bill was on the faculty at the University of Illinois (joint appointment in personality and quantitative psychology), Auburn University (quantitative psychology), and the University of Alabama (quantitative psychology with a joint appointment in applied statistics). He has also spent sabbatical years at Dalhousie University in Halifax, Nova Scotia and at New York University, and he was a visiting professor at Phillips University in Marburg, Germany.
Bill is an elected member of the Society of Multivariate Experimental Psychology (1988) and was selected to attend advanced training workshops in longitudinal data analysis and the analysis of fMRI data. He is also on the quantitative faculty (psychometrics) of the NIH sponsored Summer Training Instituite for Randomized Clinical Trials involving behavioral interventions. Bill serves routinely on the editorial boards of the Journal of Personality and Social Psychology, Personality and Social Psychology Bulletin, and the Journal of Research in Personality. He was associate editor of the Journal of Research in Personality from 1994-2000.
Bill has extensive consulting and collaborative data analytic experience and has worked on projects at the Oregon Research Institute, Georgetown Medical School, Mt. Sinai School of Medicine, and Columbia University Medical School. His major areas of expertise are longitudinal data analysis, confirmatory factor analysis, mediational models, and psychometrics.
Dr. Chaplin has substantive interests in personality psychology, but also has interests in issues involving psychometrics and the analysis of data, particularly in applied research. He is concerned with issues involving the analysis of change and the analysis of latent variables. In addition, he has worked on the appropriate analysis of data generated by designs that combine qualitative experimental variables with quantitative naturalistic ones.