This textbook describes the broadening methodology spectrum of psychological measurement in order to meet the statistical needs of a modern psychologist. The way statistics is used, and maybe even perceived, in psychology has drastically changed over the last few years; computationally as well as methodologically. R has taken the field of psychology by storm, to the point that it can now safely be considered the lingua franca for statistical data analysis in psychology. The goal of this book is to give the reader a starting point when analyzing data using a particular method, including advanced versions, and to hopefully motivate him or her to delve deeper into additional literature on the method. Beginning with one of the oldest psychometric model formulations, the true score model, Mair devotes the early chapters to exploring confirmatory factor analysis, modern test theory, and a sequence of multivariate exploratory method. Subsequent chapters present special techniques useful for modern psychological applications including correlation networks, sophisticated parametric clustering techniques, longitudinal measurements on a single participant, and functional magnetic resonance imaging (fMRI) data. In addition to using real-life data sets to demonstrate each method, the book also reports each method in three parts-- first describing when and why to apply it, then how to compute the method in R, and finally how to present, visualize, and interpret the results. Requiring a basic knowledge of statistical methods and R software, but written in a casual tone, this text is ideal for graduate students in psychology. Relevant courses include methods of scaling, latent variable modeling, psychometrics for graduate students in Psychology, and multivariate methods in the social sciences.

Using a meaning-based approach that emphasizes the “why” over the “how to,” Psychometrics: An Introduction provides thorough coverage of fundamental issues in psychological measurement. Author R. Michael Furr discusses traditional psychometric perspectives and issues including reliability, validity, dimensionality, test bias, and response bias as well as advanced procedures and perspectives including item response theory and generalizability theory. The substantially updated Third Edition includes broader and more in-depth coverage with new references, a glossary summarizing over 200 key terms, and expanded suggested readings consisting of highly relevant papers to enhance the book’s overall accessibility, scope, and usability.

Today psychometrics plays an increasingly important role in all our lives as testing and assessment occurs from preschool until retirement. This book introduces the reader to the subject in all its aspects, ranging from its early history, school examinations, how to construct your own test, controversies about IQ and recent developments in testing on the internet. In Part one of Modern Psychometrics, Rust and Golombok outline the history of the field and discuss central theoretical issues such as IQ, personality and integrity testing and the impact of computer technology and the internet. In Part two a practical step-by-step guide to the development of a psychometric test is provided. This will enable anyone wishing to develop their own test to plan, design, construct and validate it to a professional standard. This third edition has been extensively updated and expanded to take into account recent developments in the field, making it the ideal companion for those studying for the British Psychological Society’s Certificates of Competence in Testing. Modern Psychometrics combines an up to date scientific approach to the subject with a full consideration of the political and ethical issues involved in the large scale implementation of psychometrics testing in today’s highly networked society, particularly in terms of issues of diversity and internationalism. It will be useful to students and practictioners at all levels who are interested in psychometrics.

Currently there are many introductory textbooks on educational measurement and psychometrics as well as R. However, there is no single book that covers important topics in measurement and psychometrics as well as their applications in R. The Handbook of Educational Measurement and Psychometrics Using R covers a variety of topics, including classical test theory; generalizability theory; the factor analytic approach in measurement; unidimensional, multidimensional, and explanatory item response modeling; test equating; visualizing measurement models; measurement invariance; and differential item functioning. This handbook is intended for undergraduate and graduate students, researchers, and practitioners as a complementary book to a theory-based introductory or advanced textbook in measurement. Practitioners and researchers who are familiar with the measurement models but need to refresh their memory and learn how to apply the measurement models in R, would find this handbook quite fulfilling. Students taking a course on measurement and psychometrics will find this handbook helpful in applying the methods they are learning in class. In addition, instructors teaching educational measurement and psychometrics will find our handbook as a useful supplement for their course.

Providing conceptual and practical foundations in scale construction and psychometrics for producers and consumers of social/personality research, this guide covers basic principles, practices, and processes in scale construction, scale evaluation, scale use, and interpretation of research results in the context of psychological measurement. It explains fundamental concepts and methods related to dimensionality, reliability, and validity. In addition, it provides relatively non-technical introductions to special topics and advanced psychometric perspectives such as Confirmatory Factor Analysis, Generalizability Theory, and Item Response Theory. The SAGE Library in Social and Personality Psychology Methods provides students and researchers with an understanding of the methods and techniques essential to conducting cutting-edge research. Each volume within the Library explains a specific topic and has been written by an active scholar (or scholars) with expertise in that particular methodological domain. Assuming no prior knowledge of the topic, the volumes are clear and accessible for all readers. In each volume, a topic is introduced, applications are discussed, and readers are led step by step through worked examples. In addition, advice about how to interpret and prepare results for publication are presented.

Grounded in current knowledge and professional practice, this book provides up-to-date coverage of psychometric theory, methods, and interpretation of results. Essential topics include measurement and statistical concepts, scaling models, test design and development, reliability, validity, factor analysis, item response theory, and generalizability theory. Also addressed are norming and test equating, topics not typically covered in traditional psychometrics texts. Examples drawn from a dataset on intelligence testing are used throughout the book, elucidating the assumptions underlying particular methods and providing SPSS (or alternative) syntax for conducting analyses. The companion website presents datasets for all examples as well as PowerPoint slides of figures and key concepts. Pedagogical features include equation boxes with explanations of statistical notation, and end-of-chapter glossaries. The Appendix offers extensions of the topical chapters with example source code from SAS, SPSS, IRTPRO, BILOG-MG, PARSCALE, TESTFACT, and DIMTEST.

"This accessible volume presents both the mechanics of structural equation modeling (SEM) and specific SEM strategies and applications. The editor, along with an international group of contributors, and editorial advisory board are leading methodologists who have organized the book to move from simpler material to more statistically complex modeling approaches. Sections cover the foundations of SEM; statistical underpinnings, from assumptions to model modifications; steps in implementation, from data preparation through writing the SEM report; and basic and advanced applications, including new and emerging topics in SEM. Each chapter provides conceptually oriented descriptions, fully explicated analyses, and engaging examples that reveal modeling possibilities for use with readers' data. Many of the chapters also include access to data and syntax files at the companion website, allowing readers to try their hands at reproducing the authors' results"--