This book 'Essays on Contemporary Psychometrics' provides an overview of contemporary psychometrics, the science devoted to the advancement of quantitative measurement practices in psychology, education and the social sciences. The volume consists of four parts, each having several chapters on cutting-edge work in the field. Part I, General Perspectives on Psychometrics, includes expert views on topics such as psychological models vs. measurement models, using tests in decision making, artificial intelligence, and psychometric network models. Part II, Factor Analysis and Classical Test Theory, the type of psychometrics that is still used most often in the social and behavioral sciences, includes state-of-the-art contributions on test-score reliability, change-score reliability, handling missing data in principal component analysis, test equating, and conditional standard errors of measurement. Part III, Item Response Theory, the leading form of psychometrics in modern educational measurement, includes discussions of sampling from many conditional distributions, transparent score reporting, nonparametric item response theory, and targeted testing. Part IV, New Psychometrics, discusses recently developed ideas beyond classical test theory and item response theory, including topics related to computer adaptive testing, response-time modelling, validity indices, diagnostic classification models, and the sparse latent class model for ordinal measurements. Together, these four parts provide an overview of the current state-of-the-art in psychometrics in educational measurement. They are a valuable source of information for graduate students who (intend to) study psychometrics and need an overview of the field, and for researchers interested in the current developments in the field. Chapters [3], [5], [8], [16] and [19] are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

This volume is a collection of new, published and revised essays, providing a distinctive, thoroughgoing, realist approach to contemporary psychological theories, concepts, methods, and applications. The essays also offer critical analyses of antirealist trends both in and outside of mainstream psychology.

The edition of this classic text has been completely revised and updated, taking into account recent developments in the field of psychometrics. Part 1 of Modern Psychometrics outlines the background, history and controversies surrounding psychological testing. Part 2 provides a practical guide for developing a psychometric test. Modern Psychometrics forms the ideal companion for those studying for the British Psychological Society's Certificates of Competence in Testing

Contemporary Psychometrics features cutting edge chapters organized in four sections: test theory, factor analysis, structural equation modeling, and multivariate analysis. The section on test theory includes topics such as multidimensional item response theory (IRT), the relationship between IRT and factor analysis, estimation and testing of these models, and basic measurement issues that are often neglected. The factor analysis section reviews the history and development of the model, factorial invariance and factor analysis indeterminacy, and Bayesian inference for factor scores and parameter estimates. The section on structural equation modeling (SEM) includes the general algebraic-graphic rules for latent variable SEM, a survey of goodness of fit assessment, SEM resampling methods, a discussion of how to compare correlations between and within independent samples, dynamic factor models based on ARMA time series models, and multi-level factor analysis models for continuous and discrete data. The final section on multivariate analysis includes topics such as dual scaling of ordinal data, model specification and missing data problems in time series models, and a discussion of the themes that run through all multivariate methods. This tour de force through contemporary psychometrics will appeal to advanced students and researchers in the social and behavioral sciences and education, as well as methodologists from other disciplines.

Multivariate Statistical Methods: A Primer offers an introduction to multivariate statistical methods in a rigorous yet intuitive way, without an excess of mathematical details. In this fifth edition, all chapters have been revised and updated, with clearer and more direct language than in previous editions, and with more up-to-date examples, exercises, and references, in areas as diverse as biology, environmental sciences, economics, social medicine, and politics. Features • A concise and accessible conceptual approach that requires minimal mathematical background. • Suitable for a wide range of applied statisticians and professionals from the natural and social sciences. • Presents all the key topics for a multivariate statistics course. • The R code in the appendices has been updated, and there is a new appendix introducing programming basics for R. • The data from examples and exercises are available on a companion website. This book continues to be a great starting point for readers looking to become proficient in multivariate statistical methods, but who might not be deeply versed in the language of mathematics. In this edition, we provide readers with conceptual introductions to methods, practical suggestions, new references, and a more extensive collection of R functions and code that will help them to deepen their toolkit of multivariate statistical methods.

This comprehensive, interdisciplinary handbook reviews the latest methods and technologies used in automated essay evaluation (AEE) methods and technologies. Highlights include the latest in the evaluation of performance-based writing assessments and recent advances in the teaching of writing, language testing, cognitive psychology, and computational linguistics. This greatly expanded follow-up to Automated Essay Scoring reflects the numerous advances that have taken place in the field since 2003 including automated essay scoring and diagnostic feedback. Each chapter features a common structure including an introduction and a conclusion. Ideas for diagnostic and evaluative feedback are sprinkled throughout the book. Highlights of the book’s coverage include: The latest research on automated essay evaluation. Descriptions of the major scoring engines including the E-rater®, the Intelligent Essay Assessor, the IntellimetricTM Engine, c-raterTM, and LightSIDE. Applications of the uses of the technology including a large scale system used in West Virginia. A systematic framework for evaluating research and technological results. Descriptions of AEE methods that can be replicated for languages other than English as seen in the example from China. Chapters from key researchers in the field. The book opens with an introduction to AEEs and a review of the "best practices" of teaching writing along with tips on the use of automated analysis in the classroom. Next the book highlights the capabilities and applications of several scoring engines including the E-rater®, the Intelligent Essay Assessor, the IntellimetricTM engine, c-raterTM, and LightSIDE. Here readers will find an actual application of the use of an AEE in West Virginia, psychometric issues related to AEEs such as validity, reliability, and scaling, and the use of automated scoring to detect reader drift, grammatical errors, discourse coherence quality, and the impact of human rating on AEEs. A review of the cognitive foundations underlying methods used in AEE is also provided. The book concludes with a comparison of the various AEE systems and speculation about the future of the field in light of current educational policy. Ideal for educators, professionals, curriculum specialists, and administrators responsible for developing writing programs or distance learning curricula, those who teach using AEE technologies, policy makers, and researchers in education, writing, psychometrics, cognitive psychology, and computational linguistics, this book also serves as a reference for graduate courses on automated essay evaluation taught in education, computer science, language, linguistics, and cognitive psychology.

A Single Cohesive Framework of Tools and Procedures for Psychometrics and Assessment Bayesian Psychometric Modeling presents a unified Bayesian approach across traditionally separate families of psychometric models. It shows that Bayesian techniques, as alternatives to conventional approaches, offer distinct and profound advantages in achieving many goals of psychometrics. Adopting a Bayesian approach can aid in unifying seemingly disparate—and sometimes conflicting—ideas and activities in psychometrics. This book explains both how to perform psychometrics using Bayesian methods and why many of the activities in psychometrics align with Bayesian thinking. The first part of the book introduces foundational principles and statistical models, including conceptual issues, normal distribution models, Markov chain Monte Carlo estimation, and regression. Focusing more directly on psychometrics, the second part covers popular psychometric models, including classical test theory, factor analysis, item response theory, latent class analysis, and Bayesian networks. Throughout the book, procedures are illustrated using examples primarily from educational assessments. A supplementary website provides the datasets, WinBUGS code, R code, and Netica files used in the examples.

Is it possible to measure psychological attributes like intelligence, personality and attitudes and if so, how does that work? What does the term 'measurement' mean in a psychological context? This fascinating and timely book discusses these questions and investigates the possible answers that can be given response. Denny Borsboom provides an in-depth treatment of the philosophical foundations of widely used measurement models in psychology. The theoretical status of classical test theory, latent variable theory and positioned in terms of the underlying philosophy of science. Special attention is devoted to the central concept of test validity and future directions to improve the theory and practice of psychological measurement are outlined.

Clinical Psychometrics is an introduction to the long-term attempt to measure the psychiatric dimension of dementia, schizophrenia, mania, depression, anxiety, neuroticism, extraversion/introversion and health-related quality of life. The two psychometric procedures, classical factor analysis and modern item-response models, are presented for readers without any requirement for particular mathematical or statistical knowledge. The book is unique in this attempt and provides helpful background information for the dimensional approach that is being used in the forthcoming updates to the diagnostic classification systems, ICD-11 and DSM-5. The book is written for everyone who is interested in the origins and development of modern psychiatry, and who wants to be familiar with its practical possibilities; how it is possible to compare different individuals with each other, how one may determine the boundary between what is normal and what is disease, or how one may assess the clinical effect of the various forms of treatment, available to present day psychiatry.