Handbook of Item Response Theory (eBook, PDF)

Volume 1: Models
Redaktion: Linden, Wim J. van der

• Format: PDF

Produktbeschreibung

Drawing on the work of internationally acclaimed experts in the field, this first volume in a three-volume set presents all major item response models. It covers many model developments that have occurred in the field during the last 20 years.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 623
• Erscheinungstermin: 14. Oktober 2016
• Englisch
• ISBN-13: 9781466514423
• Artikelnr.: 46883454

Autorenporträt

Wim J. van der Linden is a distinguished scientist and director of research innovation at Pacific Metrics Corporation. He is also a professor emeritus of measurement and data analysis at the University of Twente. He is a past president of the Psychometric Society and National Council on Measurement in Education (NCME) and a recipient of career achievement awards from NCME, Association of Test Publishers (ATP), and American Educational Research Association (AERA). His research interests include test theory, computerized adaptive testing, optimal test assembly, parameter linking, test equating, and response-time modeling as well as decision theory and its application to problems of educational decision making. Dr. van der Linden earned a PhD in psychometrics from the University of Amsterdam.

Inhaltsangabe

Dichotomous Models. Nominal and Ordinal Models. Multidimensional and Multicomponent Models. Models for Response Times. Nonparametric Models. Models for Nonmonotone Items. Hierarchical Response Models. Generalized Modeling Approaches.

Rezensionen

"Handbook I is likely to be useful for undergraduate or graduate students who have an interest in pursuing quantitative research in educational and psychological testing, especially with datasets that contain multiple discrete outcomes. Master- and doctoral-level students seeking dissertation topics and doing literature reviews will find Handbook I a valuable resource."
~Edward H. Ip, Wake Forest School of Medicine, Journal of the American Statistical Association