Dr. Asparouhov is a member of the Mplus team. His main research interest is in numerical algorithms for latent variable model estimation. His research has appeared in a diverse mix of journals including Structural Equation Modeling: A Multidisiplinary Journal, Communications in Statistics, Econometric Theory, and the Proceedings of the American Mathematical Society.

Dr. Bandalos is Professor of educational psychology and director of the Research, Evaluation, Measurement, and Statistics Program at the University of Georgia, where she teaches courses in structural equation modeling, measurement theory, and scale development. Her research interests include the use and misuse of item parceling in structural equation modeling, applications of structural equation modeling in scale development, validity studies, and assessment and accountability. 

Dr. DiStefano is Assistant Professor at the University of South Carolina where she teaches courses in assessment and statistics. Her research interests include survey methodology, cluster analysis, and the application of structural equation modeling and measurement techniques to issues of psychological testing and child behavior.

Dr. Enders is Associate Professor at Arizona State University.  His research interests involve methodological issues related to analyses with missing data, longitudinal modeling, and growth mixture modeling.  His research has appeared in journals such as Educational and Psychological Measurement, Psychological Methods, Structural Equation Modeling: A Multidisciplinary Journal, Multivariate Behavioral Research, and Applied Measurement in Education.  Dr. Enders is a past officer of the structural equation modeling special interest group of the American Educational Research Association.  He has served on the editorial board of several methodological and applied journals, including Educational and Psychological Measurement and Psychological Methods,and has been an ad hoc reviewer for several other leading methodological journals.

Dr. Finney is Assistant Professor in the Department of Graduate Psychology at James Madison University where she teaches courses in structural equation modeling and multivariate statistics. The majority of her research involves the use of structural equation modeling to gather construct validity evidence for various self-report measures. Her other research interests include student achievement motivation and statistics education. 

Dr. Flaherty is Assistant Professor in the Department of Psychology at the University of Washington.  His research interests involve categorical and longitudinal statistical models, often within the context of substance use and dependence.  His work has appeared in journals such as the Multivariate Behavioral Research, International Journal of Behavioral Development, and Drug and Alcohol Dependence. He has been an ad hoc reviewer for several leading journals and conferences, as well as a grant reviewer.

Dr. Gagné is Assistant Professor at Georgia State University. He teaches applied statistics courses in the Department of Educational Policy Studies and conducts primarily simulation research in structural equation modeling and other statistical techniques. .

Dr. Green is Professor of measurement, statistics, and methodological studies in the Division of Psychology in Education at Arizona State University. He is leader of the Educational Psychology Program in the division. His research interests include structural equation modeling, reliability theory, and mixed modeling as they apply to educational and psychological research.

Dr. Hau is Professor and Chair of the Educational Psychology Department at the Chinese University of Hong Kong. His research centers on motivation, structural equation modeling, psychometrics, computerized testing, and adolescent suicide. He has run a great number of national-level workshops on structural equation modeling in China and has played a very active role in Hong Kong government policy formation on ability segregation of students, computerized assessment, medium of instruction, and public examination systems.

Dr. Hershberger is Professor of psychology in the Department of Psychology at California State University, Long Beach. He has published extensively in the areas of structural equation modeling, psychometric theory, behavior genetics, and sexual orientation and behavior. He is a fellow of the Royal Statistical Society and International Statistical Institute.

Dr. Kline is Associate Professor of psychology at Concordia University in Montreal. Since earning a PhD in psychology, his areas of research and writing have included the psychometric evaluation of cognitive abilities, clinical child assessment, structural equation modeling, reform of data analysis methods in the behavioral sciences, and usability engineering in computer science. He is the author of over 40 empirical studies, three books, and is the coauthor of a teacher-informant questionnaire of student behavioral and scholastic adjustment.

Dr. Kreuter is Assistant Professor in the Joint Program in Survey Methodology at the University of Maryland.  Her research interests include sampling and non-sampling errors in complex surveys, systematic measurement errors in survey response, and growth mixture modeling for non-normal outcomes.  She has published several books on data analysis using STATA, and her work has appeared in journals such as the Journal of Official Statistics.

Dr. Lawrence is Assistant Professor in the College of Health and Human Development, Pennsylvania State University. Previously he was a research professor in the College of Education, University of Alabama at Birmingham. He teaches graduate courses in regression and longitudinal data analyses. His recent and current research involves examining the behavior of general growth mixture models.

Dr. Loken is Assistant Professor in the Department of Human Development and Family Studies in the College of Health and Human Development, Pennsylvania State University. He works on latent variable models, both with continuous latent variables such as factor and SEM models, and mixture models which have categorical latent variables.  He also works in the area of item response theory, models typically used for educational measurement. In general, he focuses on the application of Bayesian methods to improve inference and inform model selection.

Dr. Lubke is Assistant Professor in the Psychology Department at the University Of Notre Dame.  Her research interests include applications of latent variable modeling and purely methodological topics. Her current applied research is mainly in the field of psychiatric genetics, with a focus on the question whether a disorder is best described in terms of qualitatively different subtypes or in terms of a continuous underlying risk factor. The methodological topics are in the area of measurement invariance, factor mixture modeling as an extension of latent class analysis, multi-group factor analysis including longitudinal analysis, analysis of categorical data, and genetic statistics. Dr. Lubke’s work has appeared in journals such as Multivariate Behavioral Research, Structural Equation Modeling, and Psychological Methods.

Dr. Marsh is Professor of educational psychology and founding director of the SELF Research Centre, University of Western Sydney, Australia, is widely published (250 journal articles, 22 chapters, 8 monographs, 275 conference papers, and widely used tests measuring self-concept, motivation, and evaluations of teaching effectiveness) and a “highly cited researcher” on ISI's list of the “world’s most cited and influential scientific authors.” His research interests include self-concept and motivational constructs, evaluations of teaching effectiveness, developmental psychology, quantitative analysis, sports psychology, peer review, peer support, and anti-bullying interventions.

Dr. Masyn is Assistant Professor in the Department of Human and Community Development at the University of California, Davis.  Her areas of specialization are discrete time survival analysis, latent variable growth modeling, and finite mixture modeling. Her work has applied in the areas of prevention science, childhood aggression, alcohol and substance abuse, and teacher retention in urban school settings.  She has been published in the Journal of Educational and Behavioral Statistics.

Dr. Mueller is Professor of Educational Research and of Public Policy and Public Administration at The George Washington University, Washington, DC, and currently serves as Chair of the Department of Educational Leadership. He is the co-editor of Structural Equation Modeling: A Second Course (2006, Information Age Publishing) and author of Basic Principles of Structural Equation Modeling: An Introduction to LISREL and EQS (1996, Springer-Verlag), among other writings. He is past chair of the American Educational Research Association's special interest group on SEM, serves on the editorial boards of several methodological and applied research journals, and conducts regular SEM training sessions for national and international audiences.

Dr. Muthén is Professor at the Graduate School of Education & Information Studies at UCLA.  He was the 1988-89 President of the Psychometric Society.  He currently has an Independent Scientist Award from the National Institutes of Health for methodology development in the alcohol field.  Dr. Muthén is one of the developers of the Mplus computer program, which implements many of his statistical procedures.  His research interests focus on the development of applied statistical methodology in areas of education and public health.  Applications in education concern achievement development while public health applications involve developmental studies in epidemiology and psychology.  Methodological areas include latent variable modeling, analysis of individual differences in longitudinal data, preventive intervention studies, analysis of categorical data, multilevel modeling, and the development of statistical software.

Dr. Soller is a Research Staff Member in the Science and Technology Division at the Institute for Defense Analyses. Her research involves applying artificial intelligence methods to analyze and assess online collaborative learning and problem solving, and providing advice on national security issues concerning distributed collaboration and learning technology. She was previously a Senior Artificial Intelligence Engineer at the MITRE Corporation, and a Project Manager at the Institute for Research in Science and Technology, Italy. She holds a Ph.D. in Artificial Intelligence from the University of Pittsburgh, has published over 35 peer reviewed articles, and sits on a number of editorial and scientific advisory boards.

Karen M. Samuelsen is an Assistant Professor in the Department of Educational Psychology's program in Research, Evaluation, Measurement, and Statistics (REMS) and Evaluation. She is also the past Assistant Director of the Center for Integrated Latent Variable Research (CILVR) at the University of Maryland. Dr. Samuelsen has been the project manager on a federally funded research grant and was awarded an NSF grant to examine computer-based performance assessments for middle school science. Her research has included the examination of differential item functioning within a mixture model context.

Dr. Stapleton is Assistant Professor in the Department of Psychology at the University of Maryland Baltimore County. Her research interests include variance estimation and statistical modeling of data that arise from complex sampling designs, as well as various issues in multilevel modeling.

Dr. Thompson is Assistant Professor of measurement, statistics, and methodological studies in the Division of Psychology in Education at Arizona State University. Her research interests include methodological techniques for large data set analysis, including structural equation modeling and multilevel modeling. She also studies the use and misuse of achievement data to inform education policy. She is Director of the EDCARE laboratory, which provides educational statistics, measurement, and evaluation services.

Dr. Tractenberg is Assistant Professor in the Department of Neurology, with secondary appointments in Biostatistics, Bioinformatics, and Biomathematics and in Psychiatry, in the Georgetown University School of Medicine. She is a biostatistician and methodologist with over ten years of experience designing and analyzing experimental research. Her areas of interest include statistical methodology and pedagogy in statistics, as well as neuropsychological instrumentation, identification of outcomes, experimental design, and longitudinal analytic methodologies. Prior to coming to Georgetown, Dr. Tractenberg spent five years at the University of California at San Diego as a biostatistician and scientist within a national consortium of Alzheimer's disease research centers. Since arriving at GU in 2002, she has collaborated on research projects on both the Main and Medical school campuses. Dr. Tractenberg was the biostatistical consultant for the General Clinical Research Center 2003-2006 and joined Neurology in 2006.

Dr. von Davier is a Principal Research Scientist at Educational Testing Service (ETS).  He developed WINMIRA, a stand-alone software program for estimating and testing a number of probabilistic models including dichotomous and polytomous mixed Rasch models.  His work has appeared in journals such as Applied Psychological Measurement, and as chapters in such books as Rasch models, foundations, recent developments, and applications (Gerhard H. Fischer & Ivo W. Molenaar, Eds.) and Applications of latent trait and latent class models in the social sciences (Jürgen Rost & Rolf Langeheine, Eds.).

Dr. Wilson is Professor of Policy, Organization, Measurement, and Evaluation at the University of California, Berkeley, where his interests focus on measurement and applied statistics.  His work spans a range of issues in measurement and assessment from the development of new statistical models for analyzing measurement data, to the development of new assessments in subject matter areas such as science education, patient-reported outcomes and child development, to policy issues in the use of assessment data in accountability systems. He has recently published three books, Constructing measures: An item response modeling approach, Explanatory item response models: A generalized linear and nonlinear approach, and Towards coherence between classroom assessment and accountability.  He is currently chairing a National Research Council committee on assessment of science achievement.  He is founding editor of a new journal: Measurement: Interdisciplinary Research and Perspectives.

Dr. Wen is Professor in the Department of Psychology, South China Normal University. Mainly educated at universities in China (mainland) and the Chinese University of Hong Kong, he studied as a visiting scholar at the University of Manchester (UK) and the University of Western Sydney (Australia) for one year, respectively. His major research interests include mathematical statistics and research methods in psychology and education, especially structural equation modeling.