This proceedings volume highlights the latest research and developments in psychometrics and statistics. It represents selected and peer-reviewed presentations given at the 85th Annual International Meeting of the Psychometric Society (IMPS), held virtually on July 13-17, 2020. The IMPS is one of the largest international meetings on quantitative measurement in education, psychology and the social sciences. It draws approximately 500 participants from around the world, featuring paper and poster presentations, symposiums, workshops, keynotes, and invited presentations. Leading experts and promising young researchers have written the included chapters. The chapters address a wide variety of topics including but not limited to item response theory, adaptive testing, Bayesian estimation, propensity scores, and cognitive diagnostic models. This volume is the 9th in a series of recent works to cover research presented at the IMPS.

The 78th Annual Meeting of the Psychometric Society (IMPS) builds on the Psychometric Society's mission to share quantitative methods relevant to psychology. The chapters of this volume present cutting-edge work in the field. Topics include studies of item response theory, computerized adaptive testing, cognitive diagnostic modeling, and psychological scaling. Additional psychometric topics relate to structural equation modeling, factor analysis, causal modeling, mediation, missing data methods, and longitudinal data analysis, among others. The papers in this volume will be especially useful for researchers in the social sciences who use quantitative methods. Prior knowledge of statistical methods is recommended. The 78th annual meeting took place in Arnhem, The Netherlands between July 22nd and 26th, 2013. The previous volume to showcase work from the Psychometric Society’s Meeting is New Developments in Quantitative Psychology: Presentations from the 77th Annual Psychometric Society Meeting (Springer, 2014).

Quantitative Psychological Research: The Complete Student's Companion expertly guides the reader through all the stages involved in undertaking quantitative psychological research: designing a study, choosing a sample of people, undertaking the study, analysing the data, and reporting the research. Accessibly written and clearly presented, the book is designed for anyone learning to conduct quantitative psychological research. It covers the full research process, from the original idea to reporting the completed study, emphasising the importance of looking beyond statistical significance in evaluating data. The book provides step-by-step guidance on choosing, interpreting and reporting the appropriate analysis, featuring worked examples and extended calculations as appendices for advanced readers. This edition features new chapters on exploratory factor analysis, logistic regression and Bayesian statistics, and has been thoroughly updated throughout to reflect the latest research practices. Care has been taken to avoid tying the book to any specific statistical software, providing readers with a thorough grounding in the basics no matter which package they go on to use. Whether you’re at the beginning of your undergraduate degree or working towards your masters or doctorate, this book will be invaluable for anyone looking to understand how to conduct quantitative psychological research.

`I often... wonder to myself whether the field needs another book, handbook, or encyclopedia on this topic. In this case I think that the answer is truly yes. The handbook is well focused on important issues in the field, and the chapters are written by recognized authorities in their fields. The book should appeal to anyone who wants an understanding of important topics that frequently go uncovered in graduate education in psychology' - David C Howell, Professor Emeritus, University of Vermont Quantitative psychology is arguably one of the oldest disciplines within the field of psychology and nearly all psychologists are exposed to quantitative psychology in some form. While textbooks in statistics, research methods and psychological measurement exist, none offer a unified treatment of quantitative psychology. The SAGE Handbook of Quantitative Methods in Psychology does just that. Each chapter covers a methodological topic with equal attention paid to established theory and the challenges facing methodologists as they address new research questions using that particular methodology. The reader will come away from each chapter with a greater understanding of the methodology being addressed as well as an understanding of the directions for future developments within that methodological area. Drawing on a global scholarship, the Handbook is divided into seven parts: Part One: Design and Inference: addresses issues in the inference of causal relations from experimental and non-experimental research, along with the design of true experiments and quasi-experiments, and the problem of missing data due to various influences such as attrition or non-compliance. Part Two: Measurement Theory: begins with a chapter on classical test theory, followed by the common factor analysis model as a model for psychological measurement. The models for continuous latent variables in item-response theory are covered next, followed by a chapter on discrete latent variable models as represented in latent class analysis. Part Three: Scaling Methods: covers metric and non-metric scaling methods as developed in multidimensional scaling, followed by consideration of the scaling of discrete measures as found in dual scaling and correspondence analysis. Models for preference data such as those found in random utility theory are covered next. Part Four: Data Analysis: includes chapters on regression models, categorical data analysis, multilevel or hierarchical models, resampling methods, robust data analysis, meta-analysis, Bayesian data analysis, and cluster analysis. Part Five: Structural Equation Models: addresses topics in general structural equation modeling, nonlinear structural equation models, mixture models, and multilevel structural equation models. Part Six: Longitudinal Models: covers the analysis of longitudinal data via mixed modeling, time series analysis and event history analysis. Part Seven: Specialized Models: covers specific topics including the analysis of neuro-imaging data and functional data-analysis.

This proceedings volume highlights the latest research and developments in psychometrics and statistics. It represents selected and peer reviewed presentations given at the 84th Annual International Meeting of the Psychometric Society (IMPS), organized by Pontificia Universidad Católica de Chile and held in Santiago, Chile during July 15th to 19th, 2019. The IMPS is one of the largest international meetings on quantitative measurement in education, psychology and the social sciences. It draws approximately 500 participants from around the world, featuring paper and poster presentations, symposiums, workshops, keynotes, and invited presentations. Leading experts and promising young researchers have written the included chapters. The chapters address a large variety of topics including but not limited to item response theory, multistage adaptive testing, and cognitive diagnostic models. This volume is the 8th in a series of recent volumes to cover research presented at the IMPS.

Robert E. McGrath offers a comprehensive survey of quantitative methods and concepts in psychology that covers everything needed at the graduate level and beyond.

The 77th Annual International Meeting of the Psychometric Society (IMPS) brought together quantitative researchers who focus on methods relevant to psychology. The conference included workshops, invited talks by well-known scholars, and presentations of submitted papers and posters. It was hosted by the University of Nebraska-Lincoln and took place between the 9th and 12th of July, 2012. The chapters of this volume are based on presentations from the meeting and reflect the latest work in the field. Topics with a primarily measurement focus include studies of item response theory, computerized adaptive testing, cognitive diagnostic modeling, and psychological scaling. Additional psychometric topics relate to structural equation modeling, factor analysis, causal modeling, mediation, missing data methods, and longitudinal data analysis, among others. The papers in this volume will be especially useful for researchers (graduate students and other quantitative researchers) in the social sciences who use quantitative methods, particularly psychologists. Most readers will benefit from some prior knowledge of statistical methods in reading the chapters.