Search

Constructing Measures introduces a way to understand the advantages and disadvantages of measurement instruments. It explains the ways to use such instruments, and how to apply these methods to develop new instruments or adapt old ones, based on item response modeling and construct references. Now in its second edition, this book focuses on the steps taken while constructing an instrument, and breaks down the'building blocks'that make up an instrument—the construct map, the design plan for the items, the outcome space, and the statistical measurement model. The material covers a variety of item formats, including multiple-choice, open-ended, and performance items, projects, portfolios, Likert and Guttman items, behavioral observations, and interview protocols. Each chapter includes an overview of the key concepts, related resources for further investigation, and exercises and activities. A variety of examples from the behavioral and social sciences and education—including achievement and performance testing, attitude measures, health measures, and general sociological scales—demonstrate the application of the material. New to this edition are additional example contexts including a cognitive/achievement example, an attitude example, and a behavioral example and new concentrations on specific measurement issues and practices such as standard-setting, computer-delivery and reporting, and going beyond the Likert response format.Constructing Measures is an invaluable text for undergraduate and graduate courses on item, test, or instrument development; measurement; item response theory; or Rasch analysis taught in a variety of departments, including education, statistics, and psychology. The book also appeals to practitioners who develop instruments, including industrial/organizational, educational, and school psychologists; health outcomes researchers; program evaluators; and sociological measurers.

D-scoring Method of Measurement presents a unified framework of classical and latent measurement referred to as D-scoring method of measurement (DSM). Provided are detailed descriptions of DSM procedures and illustrative examples of how to apply the DSM in various scenarios of measurement. The DSM is designed to combine merits of the traditional CTT and IRT for the purpose of transparency, ease of interpretations, computational simplicity of test scoring and scaling, and practical efficiency, particularly in large-scale assessments. Through detailed descriptions of DSM procedures, this book shows how practical applications of such procedures are facilitated by the inclusion of operationalized guidance for their execution using the computer program DELTA for DSM-based scoring, equating, and item analysis of test data. In doing so, the book shows how DSM procedures can be readily translated into computer source codes for other popular software packages such as R. D-scoring Method of Measurement equips researchers and practitioners in the field of educational and psychological measurement with a comprehensive understanding of the DSM as a unified framework of classical and latent scoring, equating, and psychometric analysis.

Items with ordered response categories are common in survey research, such as when respondents are asked how much they agree with certain statements. But how large are the differences between categories of response, and how well do they distinguish between respondents? This volume is the first to introduce the evaluation of rating scales to an audience of survey researchers. Evaluating Rating Scale Functioning for Survey Research provides researchers with an overview of rating scale analysis along with practical guidance on how to conduct such analyses with their own survey data. Author Stefanie A. Wind presents three categories of methods: Rasch models; non-Rasch Item Response Theory (IRT) models; and non-parametric models, together with practical examples. Tutorials, datasets, and software code (R and Facets) to accompany the book are available on the book's website.

Despite the overwhelming use of tests and questionnaires, the psychometric models for constructing these instruments are often poorly understood, leading to suboptimal measurement. Measurement Models for Psychological Attributes is a comprehensive and accessible treatment of the common and the less than common measurement models for the social, behavioral, and health sciences. The monograph explains the adequate use of measurement models for test construction, points out their merits and drawbacks, and critically discusses topics that have raised and continue to raise controversy. Because introductory texts on statistics and psychometrics are sufficient to understand its content, the monograph may be used in advanced courses on applied psychometrics, and is attractive to both researchers and graduate students in psychology, education, sociology, political science, medicine and marketing, policy research, and opinion research. The monograph provides an in-depth discussion of classical test theory and factor models in Chapter 2; nonparametric and parametric item response theory in Chapter 3 and Chapter 4, respectively; latent class models and cognitive diagnosis models in Chapter 5; and discusses pairwise comparison models, proximity models, response time models, and network psychometrics in Chapter 6. The chapters start with the theory and methods of the measurement model and conclude with a real-data example illustrating the measurement model.

Dieses Standard-Lehrbuch deckt das gesamte Themenfeld der Testtheorie und Fragebogenkonstruktion ab - von den Grundlagen im Bachelor-Studium bis zu vertiefenden Aspekten in Master-Studiengängen. Neben dem unverzichtbaren Prüfungswissen fürs Studium liefert es auch Fortgeschrittenen der psychologischen Diagnostik fundiertes Handwerkszeug für Forschungspraxis und Berufsalltag - von der Diagnostik im klinischen Setting bis hin zu Fragen des Assessments im Berufsleben. Die neue Auflage wurde grundlegend überarbeitet, aktualisiert und erweitert.Univ.-Prof. Dr. Helfried Moosbrugger, Lehrstuhl für Forschungsmethoden und Evaluation an der Goethe-Universität Frankfurt, Emeritus und Seniorprofessor; zahlreiche Methodenlehrbücher, Testentwicklungen und internationale Veröffentlichungen, langjähriger Vorsitzender der Fachgruppe Methoden und Evaluation (DGPs) sowie des Testkuratoriums der Föderation Deutscher Psychologenvereinigungen (DGPs und BDP) zur Qualitätssicherung von Testverfahren und ihren Anwendungen.Univ.-Prof. Dr. Augustin Kelava, Gründungsdirektor des Instituts Methodenzentrum in der Wirtschafts- und Sozialwissenschaftlichen Fakultät der Eberhard Karls Universität Tübingen und verantwortlich für den Bereich quantitative Methoden, zahlreiche internationale Publikationen im Bereich der Entwicklung latenter Variablenmodelle (Schätzverfahren, Modellklassen), breite Anwendungsfelder (z. B. Studienabbruchsforschung, Studierendenauswahl, Emotionsregulation), diverse wissenschaftliche Beirats-, Gutachter- und Kommissionstätigkeiten.

Recognised as the most influential publication in the field, ARM facilitates deep understanding of the Rasch model and its practical applications. The authors review the crucial properties of the model and demonstrate its use with examples across the human sciences. Readers will be able to understand and critically evaluate Rasch measurement research, perform their own Rasch analyses and interpret their results. The glossary and illustrations support that understanding, and the accessible approach means that it is ideal for readers without a mathematical background.Highlights of the new edition include: More learning tools to strengthen readers'understanding including chapter introductions, boldfaced key terms, chapter summaries, activities and suggested readings. Greater emphasis on the use of R packages; readers can download the R code from the Routledge website. Explores the distinction between numerical values, quantity and units, to understand the measurement and the role of the Rasch logit scale (Chapter 4). A new four-option data set from the IASQ (Instrumental Attitude towards Self-assessment Questionnaire) for the Rating Scale Model (RSM) analysis exemplar (Chapter 6). Clarifies the relationship between Rasch measurement, path analysis and SEM, with a host of new examples of Rasch measurement applied across health sciences, education and psychology (Chapter 10). Intended as a text for graduate courses in measurement, item response theory, (advanced) research methods or quantitative analysis taught in psychology, education, human development, business, and other social and health sciences. Professionals in these areas will also appreciate the book's accessible introduction.

Este livro clássico, citado mais de 1.900 vezes, oferece um entendimento profundo do modelo de Rasch. Os autores examinam as propriedades fundamentais do modelo e demonstram seu uso com uma variedade de exemplos nas áreas de educação, psicologia e saúde. Um glossário e numerosas ilustrações ajudam os leitores a compreenderem melhor esse modelo. Os leitores aprendem a aplicar a análise de Rasch para que possam fazer suas próprias análises e interpretar os resultados obtidos. Os autores apresentam uma visão geral acessível que não requer formação matemática. Este livro destina-se aos cursos de pós-graduação em Medição, Teoria de Resposta ao Item, Métodos de Pesquisa (avançados) ou Análise Quantitativa ministrados em Psicologia, Educação, Desenvolvimento Humano, Administração de Empresas e outras ciências sociais ou da saúde. Profissionais dessas áreas também se beneficiarão com a introdução acessível apresentada no livro.

This open access book presents a large number of innovations in the world of operational testing. It brings together different but related areas and provides insight in their possibilities, their advantages and drawbacks. The book not only addresses improvements in the quality of educational measurement, innovations in (inter)national large scale assessments, but also several advances in psychometrics and improvements in computerized adaptive testing, and it also offers examples on the impact of new technology in assessment. Due to its nature, the book will appeal to a broad audience within the educational measurement community. It contributes to both theoretical knowledge and also pays attention to practical implementation of innovations in testing technology.

Several decades of psychometric research have led to the development of sophisticated models for multidimensional test data, and in recent years, multidimensional item response theory (MIRT) has become a burgeoning topic in psychological and educational measurement. Considered a cutting-edge statistical technique, the methodology underlying MIRT can be complex, and therefore doesn't receive much attention in introductory IRT courses. However author Wes Bonifay shows how MIRT can be understood and applied by anyone with a firm grounding in unidimensional IRT modeling. His volume includes practical examples and illustrations, along with numerous figures and diagrams. Multidimensional Item Response Theory includes snippets of R code interspersed throughout the text (with the complete R code included on an accompanying website) to guide readers in exploring MIRT models, estimating the model parameters, generating plots, and implementing the various procedures and applications discussed throughout the book.

Item response theory (IRT) is widely used in education and psychology and is expanding its applications to other social science areas, medical research, and business as well. Using R for Item Response Theory Model Applications is a practical guide for students, instructors, practitioners, and applied researchers who want to learn how to properly use R IRT packages to perform IRT model calibrations with their own data.This book provides practical line-by-line descriptions of how to use R IRT packages for various IRT models. The scope and coverage of the modeling in the book covers almost all models used in practice and in popular research, including: dichotomous response modeling polytomous response modeling mixed format data modeling concurrent multiple group modeling fixed item parameter calibration modelling with latent regression to include person-level covariate(s) simple structure, or between-item, multidimensional modeling cross-loading, or within-item, multidimensional modeling high-dimensional modeling bifactor modeling testlet modeling two-tier modeling For beginners, this book provides a straightforward guide to learn how to use R for IRT applications. For more intermediate learners of IRT or users of R, this book will serve as a great time-saving tool for learning how to create the proper syntax, fit the various models, evaluate the models, and interpret the output using popular R IRT packages.

Diese Einführung in die Test- und Fragebogenkonstruktion vermittelt die notwendigen theoretischen und praktischen Kenntnisse, um einen Test oder Fragebogen fundiert entwickeln zu können. Die theoretischen Inhalte sowie die zum Verständnis wichtigen Formeln werden einfach und verständlich erklärt. Die Umsetzung der einzelnen Konstruktionsschritte wird mithilfe von Standardstatistiksoftware wie SPSS, AMOS und Winmira ausführlich dargestellt. Anhand detaillierter Erläuterungen zu den Ergebnisausgaben der Anwendungs-programme wird das Wissen gleichzeitig vertieft und eine direkte Umsetzung des Gelernten für eine praktische Problemstellung ist möglich. Das Buch gibt damit konkrete Anleitungen, wie Tests im konstruiert sowie Faktorenanalysen, Strukturgleichungsmodelle oder Rasch-Analysen angewandt werden können. Die nunmehr dritte Auflage enthält zusätzliche didaktische Elemente: Neben Zusammenfassungen sorgen nun auch Checklisten und Übersichten für besserte Strukturierung. Exkurse geben zusätzliche Hintergrundinformationen und Praxistipps helfen bei der Umsetzung. Ferner wurden weitere relevante Inhalte wie z.B. Latent-State-Trait Theorie, Cut-Off-Wertebildung oder Adaptives Testen ergänzt. AUS DEM INHALT: Einführung Theoretische Grundlagen Erstellung eines Testentwurfs Realibität Empirische Überprüfung des Testentwurfs und Normierung Exploratorische Faktorenanalyse Konfirmatorische Faktorenanalyse Probabilistische Testtheorie Probleme der Testkonstruktion ÜBER DEN AUTOR: MARKUS BÜHNER ist Inhaber der Professur für Psychologische Diagnostik am Institut für Psychologie der Karl-Franzens-Universität Graz. Vom gleichen Autor bei Pearson Studium: Statistik für Psychologen und Sozialwissenschaftler (2009, ISBN 978-3-8273-7274-1). AUF DER COMPANION-WEBSITE: Für Dozenten Alle Abbildungen elektronisch zum Download Für Studenten Lösungshinweise für die Übungsaufgaben SPSS-Datenfiles zum Nachvollziehen der Beispiele im Buch Weiterführende Links DIE ZIELGRUPPE: Studierende der Psychologie und Sozialwissenschaften.

This proceedings volume highlights the latest research and developments in psychometrics and statistics. This book compiles and expands on selected and peer reviewed presentations given at the 83rd Annual International Meeting of the Psychometric Society (IMPS), organized by Columbia University and held in New York, USA July 9th to 13th, 2018.The IMPS is one of the largest international meetings on quantitative measurement in education, psychology and the social sciences. The last couple of years it has attracted more than 500 participants and more than 250 paper presentations from researchers around the world.Leading experts in the world and promising young researchers have written the 38 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 7th in a series of recent volumes to cover research presented at the IMPS.

This volume presents a collection of chapters focused on the study of multivariate change. As people develop and change, multivariate measurement of that change and analysis of those measures can illuminate the regularities in the trajectories of individual development, as well as time-dependent changes in population averages. As longitudinal data have recently become much more prevalent in psychology and the social sciences, models of change have become increasingly important. This collection focuses on methodological, statistical, and modeling aspects of multivariate change and applications of longitudinal models to the study of psychological processes. The volume is divided into three major sections: Extension of latent change models, Measurement and testing issues in longitudinal modeling, and Novel applications of multivariate longitudinal methodology. It is intended for advanced students and researchers interested in learning about state-of-the-art techniques for longitudinal data analysis, as well as understanding the history and development of such techniques.

This proceedings book highlights the latest research and developments in psychometrics and statistics. Featuring contributions presented at the 82nd Annual Meeting of the Psychometric Society (IMPS), organized by the University of Zurich and held in Zurich, Switzerland from July 17 to 21, 2017, its 34 chapters address a diverse range of psychometric topics including item response theory, factor analysis, causal inference, Bayesian statistics, test equating, cognitive diagnostic models and multistage adaptive testing. The IMPS is one of the largest international meetings on quantitative measurement in psychology, education and the social sciences, attracting over 500 participants and 250 paper presentations from around the world every year. This book gathers the contributions of selected presenters, which were subsequently expanded and peer-reviewed.

Intended to bridge the gap between the latest methodological developments and cross-cultural research, this interdisciplinary resource presents the latest strategies for analyzing cross-cultural data. Techniques are demonstrated through the use of applications that employ cross-national data sets such as the latest European Social Survey. With an emphasis on the generalized latent variable approach, internationally prominent researchers from a variety of fields explain how the methods work, how to apply them, and how they relate to other methods presented in the book. Syntax and graphical and verbal explanations of the techniques are included. Online resources, available at www.routledge.com/9781138690271, include some of the data sets and syntax commands used in the book. Applications from the behavioral and social sciences that use real data-sets demonstrate: The use of samples from 17 countries to validate the resistance to change scale across these nations How to test the cross-national invariance properties of social trust The interplay between social structure, religiosity, values, and social attitudes A comparison of anti-immigrant attitudes and patterns of religious orientations across European countries. The second edition includes six new chapters and two revised ones presenting exciting developments in the literature of cross-cultural analysis including topics such as approximate measurement invariance, alignment optimization, sensitivity analyses, a mixed-methods approach to test for measurement invariance, and a multilevel structural equation modeling approach to explain noninvariance. This book is intended for researchers, practitioners, and advanced students interested in cross-cultural research. Because the applications span a variety of disciplines, the book will appeal to researchers and students in: psychology, political science, sociology, education, marketing and economics, geography, criminology, psychometrics, epidemiology, and public health, as well as those interested in methodology. It is also appropriate for an advanced methods course in cross-cultural analysis.

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.

This volume addresses an urgent need across multiple disciplines to broaden our understanding and use of response processes evidence of test validity. It builds on the themes and findings of the volume Validity and Validation in Social, Behavioral, and Health Sciences (Zumbo & Chan, 2014), with a focus on measurement validity evidence based on response processes. Approximately 1000 studies are published each year examining the validity of inferences made from tests and measures in the social, behavioural, and health sciences. The widely accepted Standards for Educational and Psychological Testing (1999, 2014) present five sources of evidence for validity: content-related, response processes, internal structure, relationships with other variables, and consequences of testing. Many studies focus on internal structure and relationships with other variables sources of evidence, which have a long history in validation research, known methodologies, and numerous exemplars in the literature. Far less is understood by test users and researchers conducting validation work about how to think about and apply new and emerging sources of validity evidence. This groundbreaking volume is the first to present conceptual models of response processes, methodological issues that arise in gathering response processes evidence, as well as applications and exemplars for providing response processes evidence in validation work.

This proceedings volume compiles and expands on selected and peer reviewed presentations given at the 81st Annual Meeting of the Psychometric Society (IMPS), organized by the University of North Carolina at Greensboro, and held in Asheville, North Carolina, July 11th to 17th, 2016.IMPS is one of the largest international meetings focusing on quantitative measurement in psychology, education, and the social sciences, both in terms of participants and number of presentations. The meeting built on the Psychometric Society's mission to share quantitative methods relevant to psychology, addressing a diverse set of psychometric topics including item response theory, factor analysis, structural equation modeling, time series analysis, mediation analysis, cognitive diagnostic models, and multi-level models. Selected presenters were invited to revise and expand their contributions and to have them peer reviewed and published in this proceedings volume.Previous volumes to showcase work from the Psychometric Society's meetings are New Developments in Quantitative Psychology: Presentations from the 77th Annual Psychometric Society Meeting (Springer, 2013), Quantitative Psychology Research: The 78th Annual Meeting of the Psychometric Society (Springer, 2015), Quantitative Psychology Research: The 79th Annual Meeting of the Psychometric Society, Madison, Wisconsin, 2014 (Springer, 2015), and Quantitative Psychology Research: The 80th Annual Meeting of the Psychometric Society, Beijing, 2015 (Springer, 2016).

This book reflects the current thinking and research on how consumers'perception of product risks and benefits affects their behavior. It provides the scientific, regulatory and industrial research community with a conceptual and methodological reference point for studies on consumer behavior and marketing. The contributions address various aspects of consumer psychology and behavior, risk perception and communication, marketing research strategies, as well as consumer product regulation. The book is divided into 4 parts: Product risks; Perception of product risks and benefits; Consumer behavior; Regulation and responsibility.

The research articles in this volume cover timely quantitative psychology topics, including new methods in item response theory, computerized adaptive testing, cognitive diagnostic modeling, and psychological scaling. Topics within general quantitative methodology include structural equation modeling, factor analysis, causal modeling, mediation, missing data methods, and longitudinal data analysis. These methods will appeal, in particular, to researchers in the social sciences. The 80th annual meeting took place in Beijing, China, between the 12th and 16th of July, 2015. Previous volumes to showcase work from the Psychometric Society's Meeting are New Developments in Quantitative Psychology: Presentations from the 77th Annual Psychometric Society Meeting (Springer, 2013), Quantitative Psychology Research: The 78th Annual Meeting of the Psychometric Society (Springer, 2015), and Quantitative Psychology Research: The 79th Annual Meeting of the Psychometric Society, Wisconsin, USA, 2014 (Springer, 2015).

Methodological Issues in Aging Research is the first volume in the'Notre Dame Series on Quantitative Methodology.'This new series provides practical training on the latest quantitative methods used in social and behavioral research. Each volume features contributions from leading experts in state-of-the-art techniques applicable to a selected substantive topic.The first series volume provides researchers with innovative techniques for the collection and analyses of data focusing on aging and lifespan development. The book addresses such techniques as structural equation modeling, latent class analysis, hierarchical linear growth curve modeling, dynamical systems analysis, multivariate Rasch models, survival analysis, multilevel modeling, and quantitative genetic methods. These new techniques provide: better estimates of the direct effect of environmental or treatment effects and the dynamic pattern of genetic and environmental influences on adult development more precise predictions of outcomes which in turn increase the diagnostic power of test instruments the potential for developing new treatments that take advantage of the intrinsic dynamics of the course of a disease or age-related change to enhance treatment Methodological Issues in Aging Research appeals to advanced students and researchers in lifespan development, gerontology, health psychology, and other fields related to human development. It can be used as a main or supplemental text for advanced courses related to developmental research methods.

Cited over 1900 times, this classic text facilitates a deep understanding of the Rasch model. The authors review the crucial properties of the model and demonstrate its use with a variety of examples from education, psychology, and health. A glossary and numerous illustrations aid the reader's understanding. Readers learn how to apply Rasch analysis so they can perform their own analyses and interpret the results. The authors present an accessible overview that does not require a mathematical background. Highlights of the new edition include: -More learning tools to strengthen readers'understanding including chapter introductions, boldfaced key terms, chapter summaries, activities, and suggested readings. -Divided chapters (4, 6, 7 & 8) into basic and extended understanding sections so readers can select the level most appropriate for their needs and to provide more in-depth investigations of key topics. -A website at www.routledge.com/9780415833424 that features free Rasch software, data sets, an Invariance worksheet, detailed instructions for key analyses, and links to related sources. -Greater emphasis on the role of Rasch measurement as a priori in the construction of scales and its use post hoc to reveal the extent to which interval scale measurement is instantiated in existing data sets. -Emphasizes the importance of interval level measurement data and demonstrates how Rasch measurement is used to examine measurement invariance. -Insights from other Rasch scholars via innovative applications (Ch. 9). -Extended discussion of invariance now reviews DIF, DPF, and anchoring (ch. 5). -Revised Rating Scale Model material now based on the analysis of the CEAQ (ch.6). -Clarifies the relationships between Rasch measurement, True Score Theory, and Item Response Theory by reviewing their commonalities and differences (Ch.13). -Provides more detail on how to conduct a Rasch analysis so readers can use the techniques on their own (Appendix B). Intended as a text for graduate courses in measurement, item response theory, (advanced) research methods or quantitative analysis taught in psychology, education, human development, business, and other social and health sciences, professionals in these areas also appreciate the book‘s accessible introduction.

Do statistics-heavy research papers give you a headache? Are you baffled by bias, confused by correlation, or flummoxed by F-tests? A Guide for the Statistically Perplexed is here to help! This book is designed to assist students, clinicians, and researchers in becoming familiar with statistical and research techniques by covering the essentials of the topic and drawing attention to many common problem areas.Inspired to write on this topic in reaction to mistakes he encountered in actual papers, David L. Streiner uses his trademark sense of humour and light-hearted style to explain complex statistical concepts in lucid, jargon-free language. Streiner delves into topics such as presenting data (or, conversely, how not to), statistical techniques, and more advanced procedures. To help readers detect problems with research design and interpretation, he details important ‘CRAP'(convoluted reasoning or anti-intellectual pomposity) detectors for which they should watch out.Even those with little or no background in statistics, measurement theory, or research will come out of A Guide for the Statistically Perplexed with a new understanding and appreciation of these topics.

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 thesocial sciences who use quantitative methods, particularly psychologists. Most readers will benefit from some prior knowledge of statistical methods in reading the chapters.

Intended to bridge the gap between the latest methodological developments and cross-cultural research, this interdisciplinary resource presents the latest strategies for analyzing cross-cultural data. Techniques are demonstrated through the use of applications that employ cross national data sets such as the latest European Social Survey. With an emphasis on the generalized latent variable approach, internationally–prominent researchers from a variety of fields explain how the methods work, how to apply them, and how they relate to other methods presented in the book. Syntax and graphical and verbal explanations of the techniques are included. A website features some of the data sets and syntax commands used in the book. Applications from the behavioral and social sciences that use real data-sets demonstrate: The use of samples from 17 countries to validate the resistance to change scale across these nations How to test the cross-national invariance properties of social trust The interplay between social structure, religiosity, values, and social attitudes A comparison of anti-immigrant attitudes and patterns of religious orientations across European countries. The book is divided into techniques for analyzing cross-cultural data within the generalized-latent-variable approach: multiple-group confirmatory factor analysis and multiple-group structural equation modeling; multi-level analysis; latent class analysis; and item-response theory. Since researchers from various disciplines often use different methodological approaches, a consistent framework for describing and applying each method is used so as to cross ‘methodological borders'between disciplines. Some chapters describe the basic strategy and how it relates to other techniques presented in the book, others apply the techniques and address specific research questions, and a few combine the two. A table in the preface highlights for each chapter: a description of the contents, the statistical methods used, the goal(s) of the analysis, and the data set employed. This book is intended for researchers, practitioners, and advanced students interested in cross-cultural research. Because the applications span a variety of disciplines, the book will appeal to researchers and students in: psychology, political science, sociology, education, marketing and economics, geography, criminology, psychometrics, epidemiology, and public health, as well as those interested in methodology. It is also appropriate for an advanced methods course in cross-cultural analysis.

`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 book has been replaced by The Theory and Practice of Item Response Theory, Second Edition, ISBN 978-1-4625-4775-3.

This book provides an up-to-date review of commonly undertaken methodological and statistical practices that are sustained, in part, upon sound rationale and justification and, in part, upon unfounded lore. Some examples of these'methodological urban legends', as we refer to them in this book, are characterized by manuscript critiques such as: (a)'your self-report measures suffer from common method bias'; (b)'your item-to-subject ratios are too low'; (c)'you can't generalize these findings to the real world'; or (d)'your effect sizes are too low'.Historically, there is a kernel of truth to most of these legends, but in many cases that truth has been long forgotten, ignored or embellished beyond recognition. This book examines several such legends. Each chapter is organized to address: (a) what the legend is that'we (almost) all know to be true'; (b) what the'kernel of truth'is to each legend; (c) what the myths are that have developed around this kernel of truth; and (d) what the state of the practice should be. This book meets an important need for the accumulation and integration of these methodological and statistical practices.

Written in an accessible style, this book facilitates a deep understanding of the Rasch model. Authors Bond and Fox review the crucial properties of the Rasch model and demonstrate its use with a wide range of examples including the measurement of educational achievement, human development, attitudes, and medical rehabilitation. A glossary and numerous illustrations further aid the reader's understanding. The authors demonstrate how to apply Rasch analysis and prepare readers to perform their own analyses and interpret the results. Updated throughout, highlights of the Second Edition include: a new CD that features an introductory version of the latest Winsteps program and the data files for the book's examples, preprogrammed to run using Winsteps; a new chapter on invariance that highlights the parallels between physical and human science measurement; a new appendix on analyzing data to help those new to Rasch analysis; more explanation of the key concepts and item characteristic curves; a new empirical example with data sets demonstrates the many facets of the Rasch model and other new examples; and an increased focus on issues related to unidimensionality, multidimensionality, and the Rasch factor analysis of residuals. Applying the Rasch Model is intended for researchers and practitioners in psychology, especially developmental psychologists, education, health care, medical rehabilitation, business, government, and those interested in measuring attitude, ability, and/or performance. The book is an excellent text for use in courses on advanced research methods, measurement, or quantitative analysis. Significant knowledge of statistics is not required.

This volume gathers together a set of extensions of the Rasch model, one of the most prominent models for measurement in educational research and - cial science developed by Danish mathematician Georg Rasch. The idea for this volume emerged during a meeting of the Psychometric Society in M- terey, CA. At that meeting, friends and colleagues discussed news about the impending retirement of Dr. Jurgen ¨ Rost, an important innovator and m- tor in this?eld. To recognize Jurgen's ¨ contributions, we decided to produce a collection of research on extending the Rasch model as well as embedding the Rasch model in more complex statistical models, an area that is receiving broad interest in many?elds of social sciences at the current time. This collection contains 22 chapters by recognized international experts in the?eld.Thecontributionscovertopicsrangingfromgeneralmodelextensions to application in?elds as diverse as cognition, personality, organizational and sports psychology, and health sciences and education. The Rasch model is designed for categorical data, often collected as ex- inees'responses to multiple tasks such as cognitive items from psychological tests or from educational assessments. The Rasch model's elegant mathema- cal form is suitable for extensions that allow for greater?exibility in handling complex samples of examinees and collections of tasks from di?erent domains. In these extensions, the Rasch model is enhanced by additional structural - ements that account either for di?erences between diverse populations or for di?erences among observed variables.

This book develops an intuitive understanding of IRT principles through the use of graphical displays and analogies to familiar psychological principles. It surveys contemporary IRT models, estimation methods, and computer programs. Polytomous IRT models are given central coverage since many psychological tests use rating scales.Ideal for clinical, industrial, counseling, educational, and behavioral medicine professionals and students familiar with classical testing principles, exposure to material covered in first-year graduate statistics courses is helpful. All symbols and equations are thoroughly explained verbally and graphically.

In this volume prominent scholars from both psychology and education describe how these new rules of measurement work and how they differ from the old rules. Several contributors have been involved in the recent construction or revision of a major test, while others are well-known for their theoretical contributions to measurement. The goal is to provide an integrated yet comprehensive reference source concerned with contemporary issues and approaches in testing and measurement.