Notes on Contributors to Volume 1

Amanda N. Baraldi is Assistant Professor of Psychology at Oklahoma State University. Dr. Baraldi received her doctorate in Quantitative Psychology from the Arizona State University in 2015. Dr. Baraldi's current research interests include missing data analyses, methods for assessing mediation, longitudinal growth modelling, and health and prevention research.

Tom Booth is Lecturer in Quantitative Research Methods in the Department of Psychology, University of Edinburgh. His primary methodological interests are in generalized latent variable modelling. His applied work covers individual differences, organizational, and health psychology.

Li Cai is Professor in the Advanced Quantitative Methodology program in the UCLA Graduate School of Education and Information Studies. He also serves as Director of the National Center for Research on Evaluation, Standards, and Student Testing (CRESST). In addition, he is affiliated with the UCLA Department of Psychology. His methodological research agenda involves the development of latent variable models that have wide‐ranging applications in educational, psychological, and health‐related domains of study.

Eva Ceulemans is Professor of Quantitative Data Analysis at the Faculty of Psychology and Educational Sciences, University of Leuven, Belgium. Her research focuses on the development of new techniques for modelling multivariate time series data and multigroup data, and exploring individual or group differences therein. To this end, she often combines general principles of cluster analysis with dimension reduction (principal component analysis, factor analysis) and/or regression.

Fang Fang Chen received her M.S. in psychology from Peking University, her doctoral training in Social and Quantitative Psychology from Arizona State University, and completed her post‐doctoral training at the University of North Carolina at Chapel Hill. Her methodological work focuses on measurement invariance and the bifactor model. Dr. Chen was an assistant professor of psychology at the University of Delaware, and now is a senior research biostatistician at the Nemours Center for the HealthCare Delivery Science.

David J. Ciuk is an assistant professor in the Department of Government at the Franklin & Marshall College. His academic interests center on public opinion and political psychology. His research aims to build a better understanding of the attitude formation process in the mass public. More specifically, he looks at how morals and values, policy information, and political identity affect political attitudes. He is also interested in survey experimental designs, measurement, and various public health issues.

Christine E. DeMars serves at James Madison University as a professor in the department of graduate psychology and a senior assessment specialist in the Center for Assessment and Research Studies. She teaches courses in Item Response Theory, Classical Test Theory, and Generalizability Theory, and supervises Ph.D. students. Her research interests include applied and theoretical topics in item response theory, differential item functioning, test‐taking motivation, and other issues in operational testing.

Conor V. Dolan is Professor at the VU University, Amsterdam. His research interests include: covariance structure modelling, mixture analyses, modelling of multivariate intelligence test scores, and modelling genotype‐environment interplay.

Susan Embretson is Professor of Psychology at the Georgia Institute of Technology. She has been recognized nationally and internationally for her programmatic research on integrating cognitive theory into psychometric item response theory models and into the design of measurement tasks. She has received awards from the National Council on Measurement and Education; American Educational Research Association; and the American Psychological Association Division for research and theory on item generation from cognitive theory.

Craig K. Enders is a Professor in the Department of Psychology at UCLA where he is a member of the Quantitative program area. Professor Enders teaches graduate‐level courses in missing data analyses, multilevel modelling, and longitudinal modelling. The majority of his research focuses on analytic issues related to missing data analyses and multilevel modelling. His book, Applied Missing Data Analysis, was published with Guilford Press in 2010.

David J. Hughes is an Organisational Psychologist at Manchester Business School. His research interests centre on individual differences and can be broken down into three main areas: the theory and measurement of individual differences, individual differences at work, and individual differences in financial behavior. He is interested in psychometric test evaluation and his statistical interests revolve around generalized latent variable models, in particular structural equation modelling, factor models, and other models appropriate for multivariate data with complex structures.

Paul Irwing is Professor of Psychometrics at the Manchester Business School. He chaired the Psychometrics at Work Research Group and is a director of the psychometric publishing company E‐metrixx. He has authored two research and two commercial psychometric measures. He is known for research on sex differences and pioneering work on the general factor of personality. His current research concerns the 11+ Factor Model of Personality, and the newly proposed individual difference of Personality Adaptability.

William G. Jacoby is Professor of Political Science at Michigan State University and Editor of the American Journal of Political Science. He is the former Director of the Inter‐university Consortium for Political and Social Research (ICPSR) Summer Program in Quantitative Methods of Social Research and former Editor of the Journal of Politics. Professor Jacoby’s areas of professional interest include mass political behavior and quantitative methodology (especially scaling methods, measurement theory, and statistical graphics).

Robert I. Jennrich began his work with the development of the first internationally used statistical software package BMD. His main field is statistical computing. He contributed to the development of nearly half of the 25 programs in this package. Because of this, he was a member of the 1972 Soviet‐American Scientific Exchange Delegation on Computing. Since these early days, he has published papers on stepwise linear and non‐linear regression, stepwise discriminant analysis, goodness‐of‐fit testing for covariance structure analysis, and a number of papers in factor analysis, primarily on rotation. He has recently been nominated for a lifetime achievement award, which he unfortunately didn’t get.

Ken Kelley is Professor of Information Technology, Analytics, and Operations (ITAO) and the Associate Dean for Faculty and Research in the Mendoza College of Business at the University of Notre Dame. Professor Kelley's work is on quantitative methodology, where he focuses on the development, improvement, and evaluation of statistical methods and measurement issues. Professor Kelley’s specialties are in the areas of research design, effect size estimation and confidence interval formation, longitudinal data analysis, and statistical computing. In addition to his methodological work, Professor Kelley collaborates with colleagues on a variety of important topics applying methods. Professor Kelley is an Accredited Professional Statistician™ (PStat®) by the American Statistical Association, associate editor of Psychological Methods, and recipient of the Anne Anastasi early career award by the American Psychological Association's Division of Evaluation, Measurement, & Statistics, and a fellow of the American Psychological Association.

Keke Lai is Assistant Professor of Quantitative Psychology at University of California, Merced. His research interests include structural equation modelling and multilevel modelling.

Stanley Lemeshow earned his Ph.D. at UCLA, and his MSPH at UNC. He has coauthored three textbooks: Applied Logistic Regression; Applied Survival Analysis; and Sampling of Populations – Methods and Applications. His honors include: the Wiley Lifetime Award (2003); UCLA School of Public Health Alumni Hall of Fame (2006); Fellow of the AAAS (2003); Distinguished Graduate Alumnus (Biostatistics) – UNC Graduate School Centennial (2003); Fellow of the ASA (1995); and the Statistics Section Award of the APHA (1995).

Urbano Lorenzo‐Seva is a professor in the Department of Psychology at Universitat Rovira i Virgili, Spain. He is the coauthor of FACTOR, a free‐shared software to compute exploratory factor analysis, and has published numerous articles related to this subject. His research interests include the development of new methods for exploratory data analysis, and applied psychometric research. He has taught data analysis at university level and in short courses for many years.

Bo Lu earned his Ph.D. in Statistics from the University of Pennsylvania. He is an associate professor of Biostatistics at the Ohio State University. His research expertise includes causal inference with propensity score based adjustment for observational data, survey sampling design and analysis, statistical models for missing data. He has been PIs for multiple NIH and AHRQ grants and served as the lead statistician for the Ohio Medicaid Assessment Survey series since...