Introduction to Measurement Theory bridges the gap between texts that offer a mathematically rigorous treatment of the statistical properties of measurement and ones that discuss the topic in a basic, cookbook fashion. Without overwhelming novices or boring the more mathematically sophisticated, the authors effectively cover the construction of psychological tests and the interpretation of test scores and scales; critically examine classical true-score theory; and explain theoretical assumptions and modern measurement models, controversies, and developments. Practical applications, examples, and study questions facilitate a better understanding of the uses and limitations of common measures of test reliability and validity and how to perform the basic item analysis necessary for test construction.

Introduction to measurement -- The one-parameter model -- Joint maximum likelihood parameter estimation -- Marginal maximum likelihood parameter estimation -- The two-parameter model -- The three-parameter model -- Rasch models for ordered polytomous data -- Non-Rasch models for ordered polytomous data -- Models for nominal polytomous data -- Models for multidimensional data -- Linking and equating -- Differential item functioning -- Multilevel IRT models.

Theory is the bedrock of many sciences, providing a rigorous method to advance knowledge, through testing and falsifying hypotheses about observable phenomena. To begin with, the nascent field of HCI followed the scientific method borrowing theories from cognitive science to test theories about user performance at the interface. But HCI has emerged as an eclectic interdiscipline rather than a well-defined science. It now covers all aspects of human life, from birth to bereavement, through all manner of computing, from device ecologies to nano-technology. It comes as no surprise that the role of theory in HCI has also greatly expanded from the early days of scientific testing to include other functions such as describing, explaining, critiquing, and as the basis for generating new designs. The book charts the theoretical developments in HCI, both past and present, reflecting on how they have shaped the field. It explores both the rhetoric and the reality: how theories have been conceptualized, what was promised, how they have been used and which has made the most impact in the field -- and the reasons for this. Finally, it looks to the future and asks whether theory will continue to have a role, and, if so, what this might be. Table of Contents: Introduction / The Backdrop to HCI Theory / The Role and Contribution of Theory in HCI / Classical Theories / Modern Theories / Contemporary Theory / Discussion / Summary

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.

Classical and Modern Direction of Arrival Estimation contains both theory and practice of direction finding by the leading researchers in the field. This unique blend of techniques used in commercial DF systems and state-of-the art super-resolution methods is a valuable source of information for both practicing engineers and researchers. Key topics covered are: - Classical methods of direction finding - Practical DF methods used in commercial systems - Calibration in antenna arrays - Array mapping, fast algorithms and wideband processing - Spatial time-frequency distributions for DOA estimation - DOA estimation in threshold region - Higher order statistics for DOA estimation - Localization in sensor networks and direct position estimation - Brings together in one book classical and modern DOA techniques, showing the connections between them - Contains contributions from the leading people in the field - Gives a concise and easy- to- read introduction to the classical techniques - Evaluates the strengths and weaknesses of key super-resolution techniques - Includes applications to sensor networks

This book examines test validity in the behavioral, social, and educational sciences by exploring three fundamental problems: measurement, causation and meaning. Psychometric and philosophical perspectives receive attention along with unresolved issues. The authors explore how measurement is conceived from both the classical and modern perspectives. The importance of understanding the underlying concepts as well as the practical challenges of test construction and use receive emphasis throughout. The book summarizes the current state of the test validity theory field. Necessary background on test theory and statistics is presented as a conceptual overview where needed. Each chapter begins with an overview of key material reviewed in previous chapters, concludes with a list of suggested readings, and features boxes with examples that connect theory to practice. These examples reflect actual situations that occurred in psychology, education, and other disciplines in the US and around the globe, bringing theory to life. Critical thinking questions related to the boxed material engage and challenge readers. A few examples include: What is the difference between intelligence and IQ? Can people disagree on issues of value but agree on issues of test validity? Is it possible to ask the same question in two different languages? The first part of the book contrasts theories of measurement as applied to the validity of behavioral science measures.The next part considers causal theories of measurement in relation to alternatives such as behavior domain sampling, and then unpacks the causal approach in terms of alternative theories of causation.The final section explores the meaning and interpretation of test scores as it applies to test validity. Each set of chapters opens with a review of the key theories and literature and concludes with a review of related open questions in test validity theory. Researchers, practitioners and policy makers interested in test validity or developing tests appreciate the book's cutting edge review of test validity. The book also serves as a supplement in graduate or advanced undergraduate courses on test validity, psychometrics, testing or measurement taught in psychology, education, sociology, social work, political science, business, criminal justice and other fields. The book does not assume a background in measurement.

"Psychological Testing by Theresa J. B. Kline is an accessible, easy-to-read book that effectively communicates the current concepts, trends, and controversies in the field of psychological testing. Readers are provided with an in-depth analysis of psychometrics in a format that will keep their attention and that they will be able to relate to the significance of psychological testing across numerous areas such as schools, businesses, clinical settings, military, or government." -Todd L. Chmielewski, PsycCRITIQUES, December 7, 2005 VOL. 50, NO. 49, ARTICLE 12 Psychological Testing: A Practical Approach to Design and Evaluation offers a fresh and innovative approach to students and faculty in the fields of testing, measurement, psychometrics, research design, and related areas of study. Author Theresa J.B. Kline guides readers through the process of designing and evaluating a test, while ensuring that the test meets the highest professional standards. The author uses simple, clear examples throughout and fully details the required statistical analyses. Topics include—but are not limited to—design of item stems and responses; sampling strategies; classical and modern test theory; IRT program examples; reliability of tests and raters; validation using content, criterion-related, and factor analytic approaches; test and item bias; and professional and ethical issues in testing. With the student in mind, Kline has created features that ease them into more difficult ideas, always stressing the practical use of theoretical concepts. Features include A step-by-step approach to designing a test, including construct identification, construct operationalization, collecting data, item assessment, and reliability and validity techniques Examples of data analyses with printouts and interpretation Up-to-date coverage of psychometric topics, such as difference scores, change scores, translation, computer adaptive testing, reliability and validity generalization, professional and ethical guidelines, and references IRT program outputs (dichotomous and multiple response) Coverage of traditional topics in the context of how they would be used, such as standard errors and confidence intervals Sampling approaches and their strengths and weaknesses, as well as response rates and missing data management Psychological Testing is perfectly suited as a main text for upper-level undergraduate and graduate Testing or Psychometrics courses in departments of Psychology, Education, Sociology, Management, and in the Human Services disciplines. Professional researchers, educators, and consultants will also want to add this to their libraries for up-to-date coverage of test design and evaluation techniques. "Professor Kline′s attempts to de-mystify complex measurement concepts are beautifully simplified and illustrated in her countless illustrations of practical and relevant problems for the mathematically-challenged student. This book is also a must-have for those who simply do not have the desire for the theoretical jargon used in similar textbooks but are interested in the important conceptual and practical aspects of measurement as they apply in their disciplines." —Arturo Olivarez, Jr., Texas Tech University "Kline′s Psychological Testing provides a well-written treatment of the critical issues in designing and evaluating psychometric instruments. This book will be very useful to advanced undergraduate students, graduate students, and researchers." —Richard Block, Montana State University

As part of their research activities, researchers in all areas of education develop measuring instruments, design and conduct experiments and surveys, and analyze data resulting from these activities. Educational research has a strong tradition of employing state-of-the-art statistical and psychometric (psychological measurement) techniques. Commonly referred to as quantitative methods, these techniques cover a range of statistical tests and tools. Quantitative research is essentially about collecting numerical data to explain a particular phenomenon of interest. Over the years, many methods and models have been developed to address the increasingly complex issues that educational researchers seek to address. This handbook serves to act as a reference for educational researchers and practitioners who desire to acquire knowledge and skills in quantitative methods for data analysis or to obtain deeper insights from published works. Written by experienced researchers and educators, each chapter in this handbook covers a methodological topic with attention paid to the theory, procedures, and the challenges on the use of that particular methodology. It is hoped that readers 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.

-Helps readers apply testing and measurement theories they learn in courses on psychometrics, testing and measurement and/or multivariate statistics taught in psychology, education, marketing and management. -With 22 self-standing modules instructors can pick and choose the ones that are most appropriate for their course. -Each module features an overview of a measurement issue, a step-by-step application of that theory, and two cases which depict typical dilemmas faced when applying measurement theory followed by Questions to Ponder to encourage critical examination of the issues noted in the cases. -Best practices provide recommendations for ensuring the appropriate application of the theory. -Practical questions help students assess their understanding of the topic while the examples allow them to apply the material using real data. -Each module contains exercises some of which require no computer access while others involve the use of SPSS to solve the problem and a continuing exercise incorporates many of the steps in the development of a measure of typical performance. -Recent changes in understanding measurement, with over 50 new and updated references -Explanations of why each chapter, article, or book in each module’s Further Readings section is recommended -Instructors will find suggested answers to the book’s questions and exercises; detailed solutions to the exercises; test bank with 10 multiple choice and 5 short answer questions for each module; and PowerPoint slides. Students and instructors can access SPSS data sets; additional exercises; the glossary; and additional information helpful in understanding psychometric concepts.