Description
Book SynopsisSince the development of the first intelligence test in the early 20th century, educational and psychological tests have become important measurement techniques to quantify human behavior. Focusing on this ubiquitous yet fruitful area of research, Statistical Test Theoryfor the Behavioral Sciences provides both a broad overview and a critical survey of assorted testing theories and models used in psychology, education, and other behavioral science fields.
Following a logical progression from basic concepts to more advanced topics, the book first explains classical test theory, covering true score, measurement error, and reliability. It then presents generalizability theory, which provides a framework to deal with various aspects of test scores. In addition, the authors discuss the concept of validity in testing, offering a strategy for evidence-based validity. In the two chapters devoted to item response theory (IRT), the book explores item response models, such as the Rasch model, and applications, including computerized adaptive testing (CAT). The last chapter looks at some methods used to equate tests.
Equipped with the essential material found in this book, advanced undergraduate and graduate students in the behavioral sciences as well as researchers involved in measurement and testing will gain valuable insight into the research methodologies and statistical data analyses of behavioral testing.
Trade Review"This book is a comprehensive and well-illustrated overview of the concepts and applications of statistical test theory in the social sciences. ... Various concepts and methodologies are well explained and illustrated through examples that are accompanied with data-based examples. The language of the book is simple. The prerequisite knowledge of mathematics and statistics is kept to a minimum ... The book will undoubtedly appeal to the students and application-oriented researchers in the social sciences who wish to obtain a detailed overview of statistical test theory. This book can be adopted as a textbook in advanced undergraduate and graduate courses in the social sciences and can also be comprehensively used as a part of any course in applied statistics." -Journal of the Royal Statistical Society
Table of ContentsPreface. Measurement and Scaling. Classical Test Theory. Classical Test Theory and Reliability. Estimating Reliability. Generalizability Theory. Models for Dichotomous Items. Validity and Validation of Tests. Principal Component Analysis, Factor Analysis, and Structural Equation Modeling: A Very Brief Introduction. Item Response Models. Applications of Item Response Theory. Test Equating. Answers. References. Index.
