A SPECTATOR BOOK OF THE YEAR 'History that reads like biography that reads like a novel - a fluid narrative that defies expectations and plays against type' New York Times 'Brilliant and savage' Philip Hensher An unprecedented history of the personality test conceived a century ago by a mother and her daughter - fiction writers with no formal training in psychology - and how it insinuated itself into our boardrooms, classrooms, and beyond. The Myers-Briggs Type Indicator is the most popular personality test in the world. It has been harnessed by Fortune 100 companies, universities, hospitals, churches, and the military. Its language - of extraversion vs. introversion, thinking vs. feeling - has inspired online dating platforms and Buzzfeed quizzes alike. And yet despite the test's widespread adoption, experts in the field of psychometric testing, a $500 million industry, struggle to account for its success - no less validate its results. How did the Myers-Briggs insinuate itself into our jobs, our relationships, our internet, our lives? First conceived in the 1920s by the mother-daughter team of Katherine Briggs and Isabel Briggs Myers, a pair of aspiring novelists and devoted homemakers, the Myers-Briggs was designed to bring the gospel of Carl Jung to the masses. But it would take on a life of its own, reaching from the smoke-filled boardrooms of mid-century New York to Berkeley, California, where it was honed against some of the 20th century's greatest creative minds. It would travel across the world to London, Zurich, Cape Town, Melbourne, and Tokyo; to elementary schools, nunneries, wellness retreats, and the closed-door corporate training sessions of today. Drawing from original reporting and never-before-published documents, What's Your Type? examines nothing less than the definition of the self - our attempts to grasp, categorise and quantify our personalities. Surprising and absorbing, the book, like the test at its heart, considers the timeless question: What makes you you?

KE is applied to the four major equating designs and to both Chain Equating and Post-Stratification Equating for the Non-Equivalent groups with Anchor Test Design. It will be an important reference for several groups: (a) Statisticians (b) Practitioners and (c) Instructors in psychometric and measurement programs. The authors assume some familiarity with linear and equipercentile test equating, and with matrix algebra.

Examination stress and test anxiety are pervasive problems in modern society. As the information age continues to evolve, test scores will become even more important than they are today in evaluating applicants for demanding jobs and candidates for admission into highly competitive educational programs. Because test anxiety gen- ally causes decrements in performance and undermines academic achievement, the development of effective therapeutic interventions for reducing its adverse effects will continue to be an important priority for counselors, psychologists, and educators. Alleviating test anxiety will also serve to counteract the diminished access to edu- tional and occupational opportunities that is frequently experienced by test-anxious individuals. As its title promises, this volume provides a state-of-the-art evaluation of the nature, antecedents, correlates, and consequences of examination stress and test anxiety. Professor Zeidner's cogent and comprehensive analysis of the affective, cognitive, somatic, and behavioral manifestations of test anxiety are grounded in the extensive knowledge he has gained from his own research on the assessment and treatment of test anxiety. This work has also benefitted from the author's lo- standing and productive collaboration with leading contributors to test anxiety theory and research, and his active participation in national and international conferences devoted to understanding test anxiety, including those convened by the Society for Test Anxiety Research (STAR).

Comprehensive and accessible treatment of the common measurement models for the social, behavioral, and health sciences 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. 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

This book evolved from lectures, courses and workshops on missing data and small-area estimation that I presented during my tenure as the ?rst C- pion Fellow (2000-2002). For the Fellowship I proposed these two topics as areas in which the academic statistics could contribute to the development of government statistics, in exchange for access to the operational details and background that would inform the direction and sharpen the focus of a- demic research. After a few years of involvement, I have come to realise that the separation of 'academic' and 'industrial' statistics is not well suited to either party, and their integration is the key to progress in both branches. Most of the work on this monograph was done while I was a visiting l- turer at Massey University, Palmerston North, New Zealand. The hospitality and stimulating academic environment of their Institute of Information S- ence and Technology is gratefully acknowledged. I could not name all those who commented on my lecture notes and on the presentations themselves; apart from them, I want to thank the organisers and silent attendees of all the events, and, with a modicum of reluctance, the 'grey ?gures' who kept inquiring whether I was any nearer the completion of whatever stage I had been foolish enough to attach a date.

The goal of this book is to emphasize the formal statistical features of the practice of equating, linking, and scaling. The book encourages the view and discusses the quality of the equating results from the statistical perspective (new models, robustness, fit, testing hypotheses, statistical monitoring) as opposed to placing the focus on the policy and the implications, which although very important, represent a different side of the equating practice.

The book contributes to establishing "equating" as a theoretical field, a view that has not been offered often before. The tradition in the practice of equating has been to present the knowledge and skills needed as a craft, which implies that only with years of experience under the guidance of a knowledgeable practitioner could one acquire the required skills. This book challenges this view by indicating how a good equating framework, a sound understanding of the assumptions that underlie the psychometric models, and the use of statistical tests and statistical process control tools can help the practitioner navigate the difficult decisions in choosing the final equating function.

This book provides a valuable reference for several groups: (a) statisticians and psychometricians interested in the theory behind equating methods, in the use of model-based statistical methods for data smoothing, and in the evaluation of the equating results in applied work; (b) practitioners who need to equate tests, including those with these responsibilities in testing companies, state testing agencies, and school districts; and (c) instructors in psychometric, measurement, and psychology programs.

The arrival of the computer in educational and psychological testing has led to the current popularity of adaptive testing---a testing format in which the computer uses statistical information about the test items to automatically adapt their selection to a real-time update of the test taker's ability estimate. This book covers such key features of adaptive testing as item selection and ability estimation, adaptive testing with multidimensional abilities, sequencing adaptive test batteries, multistage adaptive testing, item-pool design and maintenance, estimation of item and item-family parameters, item and person fit, as well as adaptive mastery and classification testing. It also shows how these features are used in the daily operations of several large-scale adaptive testing programs.

The cultural-test-bias hypothesis is one of the most important scien tific questions facing psychology today. Briefly, the cultural-test-bias hypothesis contends that all observed group differences in mental test scores are due to a built-in cultural bias of the tests themselves; that is, group score differences are an artifact of current psychomet ric methodology. If the cultural-test-bias hypothesis is ultimately shown to be correct, then the 100 years or so of psychological research on human differences (or differential psychology, the sci entific discipline underlying all applied areas of human psychology including clinical, counseling, school, and industrial psychology) must be reexamined and perhaps dismissed as confounded, contam inated, or otherwise artifactual. In order to continue its existence as a scientific discipline, psychology must confront the cultural-test-bias hypothesis from the solid foundations of data and theory and must not allow the resolution of this issue to occur solely within (and to be determined by) the political Zeitgeist of the times or any singular work, no matter how comprehensive. In his recent volume Bias in Mental Testing (New York: Free Press, 1980), Arthur Jensen provided a thorough review of most of the empirical research relevant to the evaluation of cultural bias in psychological and educational tests that was available at the time that his book was prepared. Nevertheless, Jensen presented only one per spective on those issues in a volume intended not only for the sci entific community but for intelligent laypeople as well."

Originally published in 1953 this book provided the first comprehensive account of methods of personality assessment by a British author. It starts with a short survey of personality theory, pointing out the difficulties in any method of testing or assessment. Next it describes the weaknesses of the common interview method. (Throughout the emphasis is on methods which are usable in educational or vocational guidance and selection, not on methods which are mainly of scientific interest.) Thereafter it takes up each main type of technique - tests based on physique or psychological measures, on expressive movement such as gestures and handwriting, tests of behaviour (including War Office Selection Board 'house party' methods), ratings and rating scales, questionnaires, and so-called projective techniques. The evidence for or against each test or method is surveyed and numerous references provided for relevant literature. Illustrative excerpts are given of many of the more promising tests, and some pictorial illustrations. British work in this field at the time is covered completely, and an attempt is made to provide a fair summary of the main contributions of American and other psychologists of the day.

This book provides an alternative method for measuring individual differences in psychological, educational, and other behavioral sciences studies. It is based on the assumptions of ordinal statistics as explained in Norman Cliff's 1996 Ordinal Methods for Behavioral Data Analysis. It provides the necessary background on ordinal measurement to permit its use to assess psychological and psychophysical tests and scales and interpret the data obtained. The authors believe that some of the behavioral measurement models used today do not fit the data or are inherently self-contradictory. Applications of these models can therefore lead to unwarranted inferences regarding the status of the derived variables. These methods can also be difficult to apply, particularly in small-sample contexts without making additional, unrealistic assumptions. Ordinal methods more closely reflect the original data, are simple to apply, and can be used in samples of any size. The book's approach is in essence a return to simple empiricism in psychological measurement. Ordinal Measurement in the Behavioral Sciences provides: *methods for analyzing test responses; *extensive discussions of ordinal approaches to analyzing data that are judgments of stimuli; *methods for treating psychological data in ways consistent with its ordinal nature so as to stimulate new developments in this area; and *ordinal test theory and the unfolding methods that are applicable to cross-cultural studies. Advanced students, researchers, and practitioners concerned with psychological measurement should find this book relevant. Measurement professionals will find it provides useful and simple methods that stimulate thought about measurement's real issues.

This introductory text describes the principles of invariant measurement, how invariant measurement can be achieved with Rasch models, and how to use invariant measurement to solve measurement problems in the social, behavioral, and health sciences. Rasch models are used throughout but a comparison of Rasch models to other item response theory (IRT) models is also provided. Written with students in mind, the manuscript was class tested to help maximize accessibility. Chapters open with an introduction and close with a summary and discussion. Numerous examples and exercises demonstrate the main issues addressed in each chapter. Key terms are defined when first introduced and in an end-of-text glossary. All of the book's analyses were conducted with the Facets program. The data sets used in the book, sample syntax files for running the Facets program, Excel files for creating item and person response functions, links to related websites, and other material are available at www.GeorgeEngelhard.com. Highlights include: A strong philosophical and methodological approach to measurement in the human sciences Demonstrations of how measurement problems can be addressed using invariant measurement Practical illustrations of how to create and evaluate scales using invariant measurement A history of measurement based on test-score and scaling traditions Previously unpublished work in analyzing rating data, the detection and measurement of rater errors, and the evaluation of rater accuracy A review of estimation methods, model-data fit, indices used to evaluate the quality of rater-mediated assessments, rater error and bias, and rater accuracy. Intended as a supplementary text for graduate or advanced undergraduate courses on measurement or test theory, item response theory, scaling theory, psychometrics, advanced measurement techniques, research methods, or evaluation research taught in education, psychology, and the social and health sciences, the book also appeals to practitioners and researchers in these fields who develop or use scales and instruments. Only a basic mathematical level is required including a basic course in statistic.

This edited volume gives a new and integrated introduction to item re sponse models (predominantly used in measurement applications in psy chology, education, and other social science areas) from the viewpoint of the statistical theory of generalized linear and nonlinear mixed models. Moreover, this new framework aHows the domain of item response mod els to be co-ordinated and broadened to emphasize their explanatory uses beyond their standard descriptive uses. The basic explanatory principle is that item responses can be modeled as a function of predictors of various kinds. The predictors can be (a) char acteristics of items, of persons, and of combinations of persons and items; they can be (b) observed or latent (of either items or persons); and they can be (c) latent continuous or latent categorical. Thus, a broad range of models can be generated, including a wide range of extant item response models as weH as some new ones. Within this range, models with explana tory predictors are given special attention, but we also discuss descriptive models. Note that the 'item responses' that we are referring to are not just the traditional 'test data, ' but are broadly conceived as categorical data from a repeated observations design. Hence, data from studies with repeated-observations experimental designs, or with longitudinal designs, mayaIso be modeled. The intended audience for this volume is rather broad."

*Invaluable school practitioner resource, revised and updated: 25% new material includes telehealth applications, cyberbullying updates, and more. *Expanded coverage of adolescent issues, such as antisocial behavior, substance use, social media, sexual orientation, and gender identity. *Practice-oriented work gives psychologists, counselors, social workers, and educators ready-to-use, downloadable tools. *Authoritative, research-based information.

Psychiatric clinicians should use rating scales and questionnaires often, for they not only facilitate targeted diagnoses and treatment; they also facilitate links to empirical literature and systematize the entire process of management. Clinically oriented and highly practical, the Handbook of Clinical Rating Scales and Assessment in Psychiatry and Mental Health is an ideal tool for the busy psychiatrist, clinical psychologist, family physician, or social worker. In this ground-breaking text, leading researchers provide reviews of the most commonly used outcome and screening measures for the major psychiatric diagnoses and treatment scenarios. The full range of psychiatric disorders are covered in brief but thorough chapters, each of which provides a concise review of measurement issues related to the relevant condition, along with recommendations on which dimensions to measure - and when. The Handbook also includes ready-to-photocopy versions of the most popular, valid, and reliable scales and checklists, along with scoring keys and links to websites containing on-line versions. Moreover, the Handbook describes well known, structured, diagnostic interviews and the specialized training requirements for each. It also includes details of popular psychological tests (such as neuropsychological, personality, and projective tests), along with practical guidelines on when to request psychological testing, how to discuss the case with the assessment consultant and how to integrate information from the final testing report into treatment. Focused and immensely useful, the Handbook of Clinical Rating Scales and Assessment in Psychiatry and Mental Health is an invaluable resource for all clinicians who care for patients with psychiatric disorders.

In this book, experts in statistics and psychometrics describe classes of linkages, the history of score linkings, data collection designs, and methods used to achieve sound score linkages. They describe and critically discuss applications to a variety of domains. They define what linking is, to distinguish among the varieties of linking and to describe different procedure for linking. Furthermore, they convey the complexity and diversity of linking by covering different areas of linking and providing diverse perspectives.

This book examines extensions of the Rasch model, one of the most researched and applied models in educational research and social science. This collection contains 22 chapters by some of the most renowned international experts in the field. They cover topics ranging from general model extensions to applications in fields as diverse as cognition, personality, organizational and sports psychology, and health sciences and education.

This is the second edition of the comprehensive treatment of statistical inference using permutation techniques. It makes available to practitioners a variety of useful and powerful data analytic tools that rely on very few distributional assumptions. Although many of these procedures have appeared in journal articles, they are not readily available to practitioners. This new and updated edition places increased emphasis on the use of alternative permutation statistical tests based on metric Euclidean distance functions that have excellent robustness characteristics. These alternative permutation techniques provide many powerful multivariate tests including multivariate multiple regression analyses.

WINNER OF THE 2007 DEGROOT PRIZE

The prominence of finite mixture modelling is greater than ever. Many important statistical topics like clustering data, outlier treatment, or dealing with unobserved heterogeneity involve finite mixture models in some way or other. The area of potential applications goes beyond simple data analysis and extends to regression analysis and to non-linear time series analysis using Markov switching models.

For more than the hundred years since Karl Pearson showed in 1894 how to estimate the five parameters of a mixture of two normal distributions using the method of moments, statistical inference for finite mixture models has been a challenge to everybody who deals with them. In the past ten years, very powerful computational tools emerged for dealing with these models which combine a Bayesian approach with recent Monte simulation techniques based on Markov chains. This book reviews these techniques and covers the most recent advances in the field, among them bridge sampling techniques and reversible jump Markov chain Monte Carlo methods.

It is the first time that the Bayesian perspective of finite mixture modelling is systematically presented in book form. It is argued that the Bayesian approach provides much insight in this context and is easily implemented in practice. Although the main focus is on Bayesian inference, the author reviews several frequentist techniques, especially selecting the number of components of a finite mixture model, and discusses some of their shortcomings compared to the Bayesian approach.

The aim of this book is to impart the finite mixture and Markov switching approach to statistical modelling to a wide-ranging community. This includes not only statisticians, but also biologists, economists, engineers, financial agents, market researcher, medical researchers or any other frequent user of statistical models. This book should help newcomers to the field to understand how finite mixture and Markov switching models are formulated, what structures they imply on the data, what they could be used for, and how they are estimated. Researchers familiar with the subject also will profit from reading this book. The presentation is rather informal without abandoning mathematical correctness. Previous notions of Bayesian inference and Monte Carlo simulation are useful but not needed.

Wim van der Linden was just given a lifetime achievement award by the National Council on Measurement in Education. There is no one more prominent in the area of educational testing.

There are hundreds of computer-based credentialing exams in areas such as accounting, real estate, nursing, and securities, as well as the well-known admissions exams for college, graduate school, medical school, and law school - there is great need on the theory of testing.

This book presents the statistical theory and practice behind constructing good tests e.g., how is the first test item selected, how are the next items selected, and when do you have enough items.

This textbook is for graduate students and research workers in social statistics and related subject areas. It follows a novel curriculum developed around the basic statistical activities: sampling, measurement and inference. The monograph aims to prepare the reader for the career of an independent social statistician and to serve as a reference for methods, ideas for and ways of studying of human populations. Elementary linear algebra and calculus are prerequisites, although the exposition is quite forgiving. Familiarity with statistical software at the outset is an advantage, but it can be developed while reading the first few chapters.

This book presents the state of the art in multilevel analysis, with an emphasis on more advanced topics. These topics are discussed conceptually, analyzed mathematically, and illustrated by empirical examples. Multilevel analysis is the statistical analysis of hierarchically and non-hierarchically nested data. The simplest example is clustered data, such as a sample of students clustered within schools. Multilevel data are especially prevalent in the social and behavioral sciences and in the biomedical sciences. The chapter authors are all leading experts in the field. Given the omnipresence of multilevel data in the social, behavioral, and biomedical sciences, this book is essential for empirical researchers in these fields.

Item response theory has become an essential component in the toolkit of every researcher in the behavioral sciences. It provides a powerful means to study individual responses to a variety of stimuli, and the methodology has been extended and developed to cover many different models of interaction. This volume presents a wide-ranging handbook to item response theory - and its applications to educational and psychological testing. It will serve as both an introduction to the subject and also as a comprehensive reference volume for practitioners and researchers. It is organized into six major sections: the nominal categories model, models for response time or multiple attempts on items, models for multiple abilities or cognitive components, nonparametric models, models for nonmonotone items, and models with special assumptions. Each chapter in the book has been written by an expert of that particular topic, and the chapters have been carefully edited to ensure that a uniform style of notation and presentation is used throughout. As a result, all researchers whose work uses item response theory will find this an indispensable companion to their work and it will be the subject's reference volume for many years to come.

The Analytic Network Process (ANP) developed by Thomas Saaty in his work on multicriteria decision making applies network structures with dependence and feedback to complex decision making. This book is a selection of applications of ANP to economic, social and political decisions, and also to technological design. The chapters comprise contributions of scholars, consultants and people concerned about the outcome of certain important decisions who applied the Analytic Network Process to determine the best outcome for each decision from among several potential outcomes. The ANP is a methodological tool that is helpful to organize knowledge and thinking, elicit judgments registered in both in memory and in feelings, quantify the judgments and derive priorities from them, and finally synthesize these diverse priorities into a single mathematically and logically justifiable overall outcome. In the process of deriving this outcome, the ANP also allows for the representation and synthesis of diverse opinions in the midst of discussion and debate,

The ANP offers economists a considerably different approach for dealing with economic problems than the usual quantitative models used. The ANP approach is based on absolute scales used to represent pairwise comparison judgments in the context of dominance with respect to a property shared by the homogeneous elements being compared. How much or how many times more does A dominate B with respect to property P? Actually people are able to answer this question by using words to indicate intensity of dominance that all of us are equipped biologically to do all the time (equal, moderate, strong, very strong, and extreme) whose conversion to numbers, validation and extension to inhomogeneous elements form the foundation of the AHP/ANP. Numerous applications of the ANP have been made to economic problems, among which prediction of the turn-around dates for the US economy in the early 1990 s and again in 2001 whose accuracy and validity were both confirmed later in the news. They were based on the process of comparisons of mostly intangible factors rather than on financial, employment and other data and statistics.

In the decade of the 1970s, item response theory became the dominant topic for study by measurement specialists. But, the genesis of item response theory (IRT) can be traced back to the mid-thirties and early forties. In fact, the term "Item Characteristic Curve," which is one of the main IRT concepts, can be attributed to Ledyard Tucker in 1946. Despite these early research efforts, interest in item response theory lay dormant until the late 1960s and took a backseat to the emerging development of strong true score theory. While true score theory developed rapidly and drew the attention of leading psychometricians, the problems and weaknesses inherent in its formulation began to raise concerns. Such problems as the lack of invariance of item parameters across examinee groups, and the inadequacy of classical test procedures to detect item bias or to provide a sound basis for measurement in "tailored testing," gave rise to a resurgence of interest in item response theory. Impetus for the development of item response theory as we now know it was provided by Frederic M. Lord through his pioneering works (Lord, 1952; 1953a, 1953b). The progress in the fifties was painstakingly slow due to the mathematical complexity of the topic and the nonexistence of computer programs.

Generalizability theory offers an extensive conceptual framework and a powerful set of statistical procedures for characterizing and quantifying the fallibility of measurements. Robert Brennan, the author, has written the most comprehensive and up-to-date treatment of generalizability theory. The book provides a synthesis of those parts of the statistical literature that are directly applicable to generalizability theory. The principal intended audience is measurement practitioners and graduate students in the behavioral and social sciences, although a few examples and references are provided from other fields. Readers will benefit from some familiarity with classical test theory and analysis of variance, but the treatment of most topics does not presume specific background.