Statistical Test Theory for the Behavioral Sciences Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences Series
Auteurs : de Gruijter Dato N. M., van der Kamp Leo J. Th.
Since 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.
Date de parution : 08-2007
15.6x23.4 cm
Date de parution : 09-2019
15.6x23.4 cm
Thèmes de Statistical Test Theory for the Behavioral Sciences :
Mots-clés :
True Score; IRT Model; Item Parameters; Rasch Model; Observed Score; 3PL Model; Conditional Error Variance; Item Response Models; Classical Test Theory; IRT Analysis; True Score Variances; Observed Score Variance; Latent Trait; Error Variance; Posterior Probability; Cut Score; Item Characteristic Curves; Item Parameter Estimates; Cat; Person Parameters; Universe Score; Graded Response Model; Normal Ogive Model; Domain Score; Construct Related Validity