Psychology: Transforming Science and Practice
In honor of the 50th Anniversary Celebration for the University of Rhode Island Department of Psychology
Dr. Gregory R. Hancock
Professor and Chair of the Measuremenet, Statistics, and Evlauation Program at the Department of Human Development and Quantitative Methodology at the University of Maryland Director of the Center of Integrated Latent Variable Research (CILVR)
Professor and Chair of the Measuremenet, Statistics, and Evlauation Program at the Department of Human Development and Quantitative Methodology at the University of Maryland
Director of the Center of Integrated Latent Variable Research (CILVR)
Will speak on Monday, December 5th, 2011 at 3:00pm- 4:15pm in CPRC West Commons, Room 45W on:
Reframing and Extending Traditional social Science Statistics Using a Likelihood/Information Paradigm: The Illustrative Case of Analysis of Variance
Abstract: For those who have acquired training in modern modeling methods, such as structural equation, latent class, or latent trait modeling, one notices that methodological practice differs considerably from that of the training in the traditional general linear modeling methods that comprise the foundation of most social science statistical training. These differences are in terms of, for example, the specification of models, the articulation of competing models, the role of researcher judgment, and the generally evidentiary nature of the modeling process. If such a paradigm is appropriate for these more sophisticated modern modeling methods, why then are they not used within the more foundational analytical scenarios? The current presentation will argue that indeed they should be, and will utilize the case of analysis of variance to illustrate how traditional social science statistical methods can be reframed and extended, thereby signifying a paradigm shift in methodological practice as well as methodological thinking.
Brief Biosketch: Gregory R. Hancock is Professor and Chair of the Measurement, Statistics and Evaluation program in the Department of Human Development and Quantitative Methodology at the University of Maryland, College Park, and Director of the Center for Integrated Latent Variable Research (CILVR). His research interests include structural equation modeling (SEM) and latent growth models, and the use of latent variables in (quasi)experimental design. His research has appeared in such journals as Psychometrika, Multivariate Behavioral Research, Structural Equation Modeling: A Multidisciplinary Journal, Psychological Bulletin, British Journal of Mathematical and Statistical Psychology, Journal of Educational and Behavioral Statistics, Educational and Psychological Measurement, Review of Educational Research, and Communications in Statistics: Simulation and Computation. He also co-edited with Ralph O. Mueller the volumes Structural Equation Modeling: A Second Course (2006) and The Reviewer's Guide to Quantitative Methods in the Social Sciences (2010), and with Karen M. Samuelsen the volume Advances in Latent Variable Mixture Models (2008). He is past chair (three terms) of the SEM special interest group of the American Educational Research Association (AERA), serves on the editorial board of a number of journals, is Associate Editor of Structural Equation Modeling: A Multidisciplinary Journal, has taught dozens of methodological workshops in the United States and abroad, and is a Fellow of AERA and the 2011 recipient of the Jacob Cohen Award for Distinguished Contributions to Teaching and Mentoring by Division 5 of the American Psychological Association. His former students are employed in academic positions around the U.S. and internationally, as well as at leading research agencies. Dr. Hancock holds a Ph.D. from the University of Washington.