This book focuses on the use of the Rasch measurement model in validation studies and in analyzing the psychometric properties of a variety of test instruments, questionnaires, and scales in international contexts. It broadly examines the development and application of Rasch modeling, providing in-depth analyses of the properties of various scales used in the fields of education, and humanities and social sciences research. The book includes exemplary works on educational research and practices that highlight recent and innovative applications, as well as theoretical and practical aspects of Rasch modeling. Readers will find it helpful to understand the latest approaches to Rasch measurement in educational research, as well as practices for future studies and quantitative research. 'This book provides a diverse set of perspectives on Rasch models from scholars across the globe. The volume is both theoretical and applied. The first section of the book provides an overview of Rasch modeling and explains the theoretical and conceptual framework underlying the Rasch model. The remainder of the book highlights multiple applications of the Rasch model within educational assessment as well as several examples of how Rasch modeling can be used for validation studies. This volume showcases the wide variety of ways in which Rasch modeling can be applied to assessment data to provide insights into students' achievement and learning and to improve instruction.'-Betsy McCoach, University of Connecticut, USA. 'A well-written collection of articles. Grouped by the theoretical and applied aspects of Rasch measurement, each chapter in this edited volume makes notable contributions to knowledge and practice. Written by leading scholars in the field, these chapters were written in a clear, succinct, and assertive manner, providing readers with up-to-date information, analyses, and debates. This book should be found in the core collection of emerging researchers and established scholars in educational measurement.'-Timothy Teo, Murdoch University, Australia.

This new edition surveys the full range of available structural equation modeling (SEM) methodologies. The book has been updated throughout to reflect the arrival of new software packages, which have made analysis much easier than in the past. Applications in a broad range of disciplines are discussed, particularly in the social sciences where many key concepts are not directly observable. This book presents SEM's development in its proper historical context-essential to understanding the application, strengths and weaknesses of each particular method. This book also surveys the emerging path and network approaches that complement and enhance SEM, and that are growing in importance. SEM's ability to accommodate unobservable theory constructs through latent variables is of significant importance to social scientists. Latent variable theory and application are comprehensively explained and methods are presented for extending their power, including guidelines for data preparation, sample size calculation and the special treatment of Likert scale data. Tables of software, methodologies and fit statistics provide a concise reference for any research program, helping assure that its conclusions are defensible and publishable.

This book is a strenuous critique of the misinterpretation of statistical knowledge of populations in mainstream psychology, exploring the implications of assuming that those statistics constitute scientific knowledge of individuals. It investigates the essential nature and historical roots of this interpretive practice, and documents the lack of change in mainstream thinking despite previous critiques of the practice. The author contends that prevailing interpretive traditions result in bad science, in that invalid claims are made to knowledge of individuals. He also discusses the socio-ethical problems resulting from this misinterpretation of statistics, where psychological practitioners unjustifiably endorse interventions in the lives of individuals. Lamiell urges psychologists to abandon the aggregate statistical methods which he argues have transformed the field into 'psycho-demography,' and to embrace instead alternative research methods that are logically suited to gaining scientific knowledge about the psychological functioning of individuals. This book concludes by highlighting some of the currently available methodological alternatives, as well as discussing some enduring conceptual impediments to the serious consideration of those alternatives.

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.

This book applies Rasch measurement theory to the fields of education, psychology, sociology, marketing and health outcomes in order to measure various social constructs. The chief focus is on first principles of both the theory and its applications. Because software is readily available to carry out analyses of real data, numerous small examples are provided in the book. The software used in these examples, and which is helpful in working through the text, is RUMM2030 (Rasch unidimensional models for measurement). The book's main goals are to equip researchers with the confidence they need in order to be in control of the analysis and interpretation of data, and to make professional rather than primarily statistical decisions mechanically. Because statistical principles are necessarily involved, reviews of the requisite statistics are provided in the Appendix. The content is based on courses that have been taught both online and in intensive form for over two decades. Although first principles are emphasised, much of the book is based on research conducted by the two authors and their colleagues.

This is a story about madness. It all starts when journalist Jon Ronson is contacted by a leading neurologist. She and several colleagues have recently received a cryptically puzzling book in the mail, and Jon is challenged to solve the mystery behind it.

This book focuses on quantitative survey methodology, data collection and cleaning methods. Providing starting tools for using and analyzing a file once a survey has been conducted, it addresses fields as diverse as advanced weighting, editing, and imputation, which are not well-covered in corresponding survey books. Moreover, it presents numerous empirical examples from the author's extensive research experience, particularly real data sets from multinational surveys.

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.

This book explores the fundamentals of multidimensional scaling (MDS) and how this analytic method can be used in applied setting for educational and psychological research. The book tries to make MDS more accessible to a wider audience in terms of the language and examples that are more relevant to educational and psychological research and less technical so that the readers are not overwhelmed by equations. The goal is for readers to learn the methods described in this book and immediately start using MDS via available software programs. The book also examines new applications that have previously not been discussed in MDS literature. It should be an ideal book for graduate students and researchers to better understand MDS. Fundamentals of Applied Multidimensional Scaling for Educational and Psychological Research is divided into three parts. Part I covers the basic and fundamental features of MDS models pertaining to applied research applications. Chapters in this section cover the essential features of data that are typically associated with MDS analysis such as preference ration or binary choice data, and also looking at metric and non-metric MDS models to build a foundation for later discussion and applications in later chapters. Part II examines specific MDS models and its applications for education and psychology. This includes spatial analysis methods that can be used in MDS to test clustering effect of items and individual differences MDS model (INDSCAL). Finally, Part III focuses on new applications of MDS analysis in these research fields. These new applications consist of profile analysis, longitudinal analysis, mean-level change, and pattern change. The book concludes with a historical review of MDS development as an analytical method and a look to future directions.

This graduate-level textbook is a tutorial for item response theory that covers both the basics of item response theory and the use of R for preparing graphical presentation in writings about the theory. Item response theory has become one of the most powerful tools used in test construction, yet one of the barriers to learning and applying it is the considerable amount of sophisticated computational effort required to illustrate even the simplest concepts. This text provides the reader access to the basic concepts of item response theory freed of the tedious underlying calculations. It is intended for those who possess limited knowledge of educational measurement and psychometrics. Rather than presenting the full scope of item response theory, this textbook is concise and practical and presents basic concepts without becoming enmeshed in underlying mathematical and computational complexities. Clearly written text and succinct R code allow anyone familiar with statistical concepts to explore and apply item response theory in a practical way. In addition to students of educational measurement, this text will be valuable to measurement specialists working in testing programs at any level and who need an understanding of item response theory in order to evaluate its potential in their settings.

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 new English translation and 100th anniversary annotated edition of Psychodiagnostics, the only book published by Hermann Rorschach, showcases Rorschach's empiricism and the wide-ranging flexibility of his thinking - and thus helps us to understand why his iconic inkblot test has survived for a century and is still being used around the world, with the support of a strong evidence base. The expert translation team have collaborated closely to create an accessible rendition of Hermann Rorschach's presentation of the inkblot test that resulted from his empirical research experiments. Also included in this edition is the case study lecture on new developments in the test that Rorschach gave to the Swiss Psychoanalytic Society in 1922, just six weeks before his premature death. His book and the lecture are each accompanied by annotations for the first time, looking backward to the sources of Rorschach's terminology and also forward to how the test is used today. Drawings and photographs from the Rorschach Archive as well as introductory chapters on the history of the translation and the creation of Psychodiagnostics bring the story of this important figure and his work to life. This volume is essential reading for both historians and contemporary users of the inkblot test and anyone interested in exploring personality testing.

The goal of this guide and manual is to provide a practical and brief overview of the theory on computerized adaptive testing (CAT) and multistage testing (MST) and to illustrate the methodologies and applications using R open source language and several data examples. Implementation relies on the R packages catR and mstR that have been already or are being developed by the first author (with the team) and that include some of the newest research algorithms on the topic. The book covers many topics along with the R-code: the basics of R, theoretical overview of CAT and MST, CAT designs, CAT assembly methodologies, CAT simulations, catR package, CAT applications, MST designs, IRT-based MST methodologies, tree-based MST methodologies, mstR package, and MST applications. CAT has been used in many large-scale assessments over recent decades, and MST has become very popular in recent years. R open source language also has become one of the most useful tools for applications in almost all fields, including business and education. Though very useful and popular, R is a difficult language to learn, with a steep learning curve. Given the obvious need for but with the complex implementation of CAT and MST, it is very difficult for users to simulate or implement CAT and MST. Until this manual, there has been no book for users to design and use CAT and MST easily and without expense; i.e., by using the free R software. All examples and illustrations are generated using predefined scripts in R language, available for free download from the book's website.

This book traces the theory and methodology of multivariate statistical analysis and shows how it can be conducted in practice using the LISREL computer program. It presents not only the typical uses of LISREL, such as confirmatory factor analysis and structural equation models, but also several other multivariate analysis topics, including regression (univariate, multivariate, censored, logistic, and probit), generalized linear models, multilevel analysis, and principal component analysis. It provides numerous examples from several disciplines and discusses and interprets the results, illustrated with sections of output from the LISREL program, in the context of the example. The book is intended for masters and PhD students and researchers in the social, behavioral, economic and many other sciences who require a basic understanding of multivariate statistical theory and methods for their analysis of multivariate data. It can also be used as a textbook on various topics of multivariate statistical analysis.

This book addresses challenges in the theoretically and empirically adequate assessment of competencies in educational settings. It presents the scientific projects of the priority program "Competence Models for Assessing Individual Learning Outcomes and Evaluating Educational Processes," which focused on competence assessment across disciplines in Germany. The six-year program coordinated 30 research projects involving experts from the fields of psychology, educational science, and subject-specific didactics. The main reference point for all projects is the concept of "competencies," which are defined as "context-specific cognitive dispositions that are acquired and needed to successfully cope with certain situations or tasks in specific domains" (Koeppen et al., 2008, p. 62). The projects investigate different aspects of competence assessment: The primary focus lies on the development of cognitive models of competencies, complemented by the construction of psychometric models based on these theoretical models. In turn, the psychometric models constitute the basis for the construction of instruments for effectively measuring competencies. The assessment of competencies plays a key role in optimizing educational processes and improving the effectiveness of educational systems. This book contributes to this challenging endeavor by meeting the need for more integrative, interdisciplinary research on the structure, levels, and development of competencies.

This book addresses problems and challenges that face educational measurement at a time when multipurpose usage of observational data from educational assessments, tests and international surveys has become a growing global trend. While the construction of educational measures and use of educational data offer many opportunities, they also require awareness of the numerous threats to validity and methods of reducing such threats. Written by leading international scholars, the book demonstrates the complexity of educational measurement by addressing three broad and interrelated topics. The first part discusses cognitive abilities, including studies on fluid intelligence, its improvement and its links to aptitude tests for admission to higher education. The second part focuses on the effects of school and teacher-related factors on school outcomes at individual and group levels, and uses international studies to analyze causes. The third part presents analytical techniques and measurement methods to improve reliability, for example factor analysis using Bayesian estimators, bi-factor analysis, model misfit and solutions, and discusses balance issues in reporting test results. The book provides examples of state-of-the-art analytical techniques for pursuing fundamental research problems, and the latest advances in measurement methods, with a focus on validity improvement. Eminent researchers discuss and provide insights into questions such as: Is it possible to train individuals to think at a higher level than normal for their age? What determines prospective preschool teachers' skill to perceive mathematics-related preschool situations? Can international indicator design and instruments be improved to use trends and national context variables more efficiently? Can indicator data at national, school and class levels be compared easier? Are value-added measures of teacher effectiveness valid when it comes to hiring and promoting teachers? Is money better spent on teacher training than on smaller class-size? How do theory and empirical statistical data intertwine in building structures of understanding? This book is inspired by the career and personal influence of the Swedish scholar Professor Jan-Eric Gustafsson, renowned for his research on individual differences, especially the structure of cognitive abilities, and on the effects of education on knowledge and skills.

What makes a fascist? Are there character traits that make someone more likely to vote for the far right? The Authoritarian Personality, written in the shadow of Fascism and the Holocaust, looked to analyse the rise of Fascism in Europe through the specific psychological traits that make people prone to authoritarianism. Based on extensive empirical studies of Americans conducted by a team which included the leading member of the Frankfurt School Theodor Adorno, The Authoritarian Personality ranked a range of character traits on what it called the 'F scale' (F for fascist). These included conventionalism, anti-intellectualism, superstition and occultism, power and toughness, destructiveness and cynicism, projectivity, and exaggerated concerns over sex. The Authoritarian Personality is not only one of the most influential works of social psychology ever written, it also marks a milestone in the development of Adorno's thought, showing him grabbling with the problem of fascism and the reasons for Europe's turn to reaction. Over half a century later and with the rise of right-wing populism and the reemergence of the far-right in recent years, this hugely influential study remains as insightful and relevant as ever.

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).

This book serves as an up-to-date Rorschach primer and elaborates on the various applications of Rorschach assessment for adolescents with respect to differential diagnosis, forensic consultation, and therapeutic assessment. It opens with three chapters that provide readers with a basic overview and introduction to the topics integrated throughout the text. The first reviews the development and foundations of the Rorschach Inkblot Method; the second discusses key issues in the assessment of adolescents, with particular attention to differentiating patterns of psychopathology from normal developmental variations; and the third presents general considerations in using performance-based assessment instruments in the assessment of personality functioning in adolescence. Later chapters explore the current status of the Rorschach Inkblot Method with respect to theoretical formulations, research findings, and practice guidelines. The final chapter draws on information in the preceding chapters to present a model for Rorschach assessment of adolescents. This model is designed to facilitate accurate and useful formulations of personality functioning that contribute substantially to advancing responsible adolescent development.

This second edition of Irving Weiner's classic comprehensive, clinician-friendly guide to utilizing the Rorschach for personality description has been revised to reflect both recent modifications in the Rorschach Comprehensive System and new evidence concerning the soundness and utility of Rorschach assessment. It integrates the basic ingredients of structural, thematic, behavioral, and sequence analysis strategies into systematic guidelines for describing personality functioning. It is divided into three parts. Part I concerns basic considerations in Rorschach testing and deals with conceptual and empirical foundations of the inkblot method and with critical issues in formulating and justifying Rorschach inferences. Part II is concerned with elements of interpretation that contribute to thorough utilization of data in a Rorschach protocol: the Comprehensive System search strategy; the complementary roles of projection and card pull in determining response characteristics; and the interpretive significance of structural variables, content themes, test behaviors, and the sequence in which various response characteristics occur. Each of the chapters presents and illustrates detailed guidelines for translating Rorschach findings into descriptions of structural and dynamic aspects of personality functioning. The discussion throughout emphasizes the implications of Rorschach data for personality assets and liabilities, with specific respect to adaptive and maladaptive features of the manner in which people attend to their experience, use ideation, modulate affect, manage stress, view themselves, and relate to others. Part III presents 10 case illustrations of how the interpretive principles delineated in Part II can be used to identify assets and liabilities in personality functioning and apply this information in clinical practice. These cases represent persons from diverse demographic backgrounds and demonstrate a broad range of personality styles and clinical issues. Discussion of these cases touches on numerous critical concerns in arriving at different diagnoses, formulating treatment plans, and elucidating structural and dynamic determinants of behavior.

The government performance movement has been in full swing for decades around the world. So, why do so many public programs and organizations continue to underperform? A major reason is that measuring the types of performance that people value most - real outcomes for citizens - continues to be an elusive goal. And why is performance measurement so difficult? Because performance managers have not taken full advantage of the tools and knowledge available in the field of program evaluation; the worlds of performance measurement and program evaluation have much to learn from each other, but they remain largely separate for reasons of history, politics, and inertia. Improving Public Services spotlights recent advances in the theory and practice of performance measurement with potential to bridge the divide. As the text's essays, case studies, and comparative analyses demonstrate, many of the challenges to outcome-based performance measurement are similar across national and cultural boundaries. And many of these challenges are amenable to solutions drawn from program evaluation, especially program theory as captured in logic models. Key issues addressed include designing and implementing high-performance contracts, using administrative data to measure performance and evaluate program effectiveness, minimizing the unintended consequences of performance-based incentive schemes, measuring qualities of governance as well as service delivery, and fitting performance systems to different institutional settings. The authors offer insights relevant to charitable organizations, private service providers, international bodies, municipalities, states, and national governments in developed, developing, and transitional countries. As the global debate over performance management rages on, this volume points to promising directions for future research and practice at the intersection of program evaluation and outcome-based public management.

While confidential informants (CI's) can play a crucial role in police investigations, they also have the potential to cause great harm if they are dishonest. The process by which police agencies qualify a CI to work and the strength of agency policy may be the source of the problem. This Brief examines the integrity problem involving CIs in police operations within the United States, provides an overview of pitfalls and problems related to veracity and informant integrity including the difficulties in detecting when a CI is lying, and compares the provisions of actual published police policy to the model CI policy published by the International Association of Chiefs of Police (IACP). The analysis shows a wide divergence between actual police policy and the national standard promulgated by the IACP. The Brief provides policy recommendations for improving use of CIs that can potentially reduce or eliminate integrity problems that can lead to organizational accidents such as wrongful arrests and convictions, injuries or deaths. Some Courts have issued measures to ensure that information received from CIs is reliable by examining sworn testimony and documents related to their work. However, as this Brief explores, this judicial effort arises only after a police operation has taken place, and the use of force - even deadly force-has already been employed. The author proposes integrity testing beforehand, which would allow police to have a greater understanding of a CI's motivation, ability and veracity when conducting law enforcement operations. In addition, there are aspects of police policy that can enhance CI management such as training, supervision and entrapment that can further guard against integrity problems. Although integrity testing is not flawless, it does interpose an additional step in the CI management process that can help guard against wrongful conviction and perjury that harms the judicial process.

This volume presents contributions on handling data in which the postulate of independence in the data matrix is violated. When this postulate is violated and when the methods assuming independence are still applied, the estimated parameters are likely to be biased, and statistical decisions are very likely to be incorrect. Problems associated with dependence in data have been known for a long time, and led to the development of tailored methods for the analysis of dependent data in various areas of statistical analysis. These methods include, for example, methods for the analysis of longitudinal data, corrections for dependency, and corrections for degrees of freedom. This volume contains the following five sections: growth curve modeling, directional dependence, dyadic data modeling, item response modeling (IRT), and other methods for the analysis of dependent data (e.g., approaches for modeling cross-section dependence, multidimensional scaling techniques, and mixed models). Researchers and graduate students in the social and behavioral sciences, education, econometrics, and medicine will find this up-to-date overview of modern statistical approaches for dealing with problems related to dependent data particularly useful.

This book provides an introduction to test equating, scaling and linking, including those concepts and practical issues that are critical for developers and all other testing professionals. In addition to statistical procedures, successful equating, scaling and linking involves many aspects of testing, including procedures to develop tests, to administer and score tests and to interpret scores earned on tests. Test equating methods are used with many standardized tests in education and psychology to ensure that scores from multiple test forms can be used interchangeably. Test scaling is the process of developing score scales that are used when scores on standardized tests are reported. In test linking, scores from two or more tests are related to one another. Linking has received much recent attention, due largely to investigations of linking similarly named tests from different test publishers or tests constructed for different purposes. In recent years, researchers from the education, psychology and statistics communities have contributed to the rapidly growing statistical and psychometric methodologies used in test equating, scaling and linking. In addition to the literature covered in previous editions, this new edition presents coverage of significant recent research. In order to assist researchers, advanced graduate students and testing professionals, examples are used frequently and conceptual issues are stressed. New material includes model determination in log-linear smoothing, in-depth presentation of chained linear and equipercentile equating, equating criteria, test scoring and a new section on scores for mixed-format tests. In the third edition, each chapter contains a reference list, rather than having a single reference list at the end of the volume The themes of the third edition include: * the purposes of equating, scaling and linking and their practical context * data collection designs * statistical methodology * designing reasonable and useful equating, scaling, and linking studies * importance of test development and quality control processes to equating * equating error, and the underlying statistical assumptions for equating

This unique collection of chapters from world experts on person-centered outcome (PCO) measures addresses the following critical questions: Can individual experiences be represented in measurements that do not reduce unique differences to meaningless uniformity? How person-centric are PCO measures? Are PCO measurements capable of delivering the kind of quality assured quantification required for high-stakes decision making? Are PCO measures likely to support improved health care delivery? Have pivotal clinical studies failed to deliver treatments for diseases because of shortcomings in the PCO measures used? Are these shortcomings primarily matters of precision and meaningfulness? Or is the lack of common languages for communicating outcomes also debilitating to quality improvement, research, and the health care economy? Three key issues form an urgent basis for further investigation. First, the numbers generated by PCO measures are increasingly used as the central dependent variables upon which high stakes decisions are made. The rising profile of PCO measures places new demands for higher quality information from scale and test construction, evaluation, selection, and interpretation. Second, PCO measurement science has well-established lessons to be learned from those who have built and established the science over many decades. Finally, the goal in making a PCO measurement is to inform outcome management. As such, it is vitally important that key stakeholders understand that, over the last half century, developments in psychometrics have refocused measurement on illuminating clinically important individual differences in the context of widely reproduced patterns of variation in health and functioning, comparable scale values for quality improvement, and practical explanatory models. This book's audience includes anyone interested in person-centered care, including healthcare researchers and practitioners, policy makers, pharmaceutical industry representatives, clinicians, patient advocates, and metrologists. This is an open access book.