C. Mitchell Dayton is Professor Emeritus in the EDMS Department at the University of Maryland.  For more than 20 years, he has pursued a research interest in latent class analysis and in 1999 he published a Sage book dealing with latent class scaling models.  Recently, he has focused on model comparison procedures with a special interest in approaches based on information theory and Bayes factors. His research has appeared in journals such as The Journal of The American Statistical Association, Psychometrika, American Statistician, Multivariate Behavioral Research, Applied Psychological Measurement, Journal of Educational and Behavioral Statistics, British Journal of Mathematical and Statistical Psychology, Psychological Methods, and Journal of Educational Measurement.

Gregory R. Hancock is Professor and Chair in the Department of Measurement, Statistics and Evaluation 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 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 of the SEM special interest group of the American Educational Research Association (three terms), serves on the editorial board of a number of journals including Structural Equation Modeling: A Multidisciplinary Journal, and has taught dozens of SEM workshops in the United States, Canada, and abroad. Dr. Hancock holds a Ph.D. from the University of Washington.  He can be reached via email at: ghancock@umd.edu.

Jeffrey Harring is an Assistant Professor in the Department of Measurement, Statistics and Evaluation at College Park. He has his Ph.D. from the Quantitative Methods in Education program at University of Minnesota. His research has been primarily concerned with statistical modeling of multivariate longitudinal/repeated measures data. Recent work has been on Nonlinear Mixed Effects Mixture (NLMM) models, which cluster individuals based on characteristics of their growth trajectories and hence represent the confluence of nonlinear mixed effects models and finite mixture models. These methods extend current linear mixture model methodology to include intrinsically nonlinear functions, and also may be extended to latent classes.

Amy Hendrickson is an adjunct Assistant Professor in the Department of Measurement, Statistics and Evaluation at College Park, and currently works for the College Board. She received her M.S. in Educational Psychology from Iowa State University in 1997 and her Ph.D. in Educational Measurement and Statistics in 2002 from the University of Iowa. Her research interests include test equating and scaling, polytomous item response theory, and computerized adaptive testing.

Hong Jiao is an Assistant Professor in the Department of Measurement, Statistics, and Evaluation at the University of Maryland. She joined the faculty of EDMS in Fall 2007 after working as a psychometrician on K-12 state assessment programs for about four years. Before working full time in psychometrics, she studied at the Florida State University for her doctoral degree in Measurement, Statistics, and Evaluation. Prior to her graduate studies in the United States, she taught ESL in the College of Foreign Languages at Shanghai Jiao Tong University in China, where she completed her M.A in Linguistics and Applied Linguistics and her B.S. in English for Science and Technology.

George Macready, Professor, has primary interests in measurement theory and research design. He has published research in Applied Psychological Measurement, Journal of Educational Statistics, Psychometrika, The Journal of The American Statistical Association, British Journal of Mathematical and Statistical Psychology, Journal of Educational Measurement, Educational and Psychological Measurement, Psychological Bulletin, and Journal of Educational Psychology. His current interests are in latent class modeling, assessment of model fit, and adaptive testing.

Robert J. Mislevy joined the EDMS department as Professor in 2001, after 16 years at Educational Testing Service where he was a Distinguished Research Scientist in the Division of Statistics and Psychometrics Research.  His research interests center on applying recent developments in statistical methodology and cognitive research to practical problems in educational and psychological measurement.  Dr. Mislevy has received numerous awards including the Raymond B. Cattell Early Career Award for Programmatic Research, the National Council of Measurement in Education’s Triennial Award and the National Council of Measurement's Award for Career Contributions to Educational Measurement. He has been president of the Psychometric Society and was nominated as a Fellow of the American Psychological Association. He has served as a member on two committees of the National Academy of Sciences concerning assessment instruction and cognitive psychology, and was a primary author of final report of the National Assessment Governing Board's Design Feasibility Team.

Andre A. Rupp joined the EDMS faculty as Assistant Professor in 2008, after started his academic career at the University of Ottawa in Canada followed by a two-year visiting professorship at the Institute for Educational Progress in Berlin, Germany, where he worked as part of an interdisciplinary team on developing national standards-based assessments for English as a first foreign language. His current research interests center around cognitively-grounded assessment approaches and associated statistical models, which broadly fall under the umbrella terms diagnostic measurement / cognitively diagnostic assessment and diagnostic classification models (DCMs) / cognitive diagnosis models. He has recently co-authored a book on this topic (Diagnostic Measurement: Theory, Methods, and Applications) with Jonathan Templin and Robert Henson. He is currently involved in two related research strands in the area of diagnostic measurement, the first centering around developing principled diagnostic assessment approaches for modeling learning progressions of complex skill sets in games- and simulation-based learning environments. The second research strand concerns describing and investigating the theoretical potential and practical limitations of DCMs and related modern multivariate measurement models more generally.