Bayesian item response modeling. Theory and applications.

Autor/in	Fox, Jean-Paul
Titel	Bayesian item response modeling. Theory and applications.
Quelle	New York, NY u.a.: Springer (2010), XIV, 313 S. PDF als Volltext (1); PDF als Volltext (2) Link als defekt meldenVerfügbarkeit
Reihe	Statistics for social and behavioral sciences
Beigaben	grafische Darstellungen; Literatur- und URL-Angaben S. [289]-307
Zusatzinformation	Inhaltsverzeichnis Verlagsangaben Inhaltsangabe
Sprache	englisch
Dokumenttyp	online; gedruckt; Monographie
ISBN	1-4419-0741-6; 978-1-4419-0741-7
DOI	10.1007/978-1-4419-0742-4
Schlagwörter	Mehrebenenanalyse; Methode; Multivariate Analyse; TIMSS (Third International Mathematics and Science Study); Sozialforschung; Item-Response-Theory; Testmethodik; Testtheorie; Grundschule; Schüler; Leistungsbeurteilung; Schülerleistung; Lehrbuch; Datenanalyse; Mathematische Kompetenz; Computerunterstütztes Verfahren; Messverfahren; Anwendungsbeispiel; Modell; Statistische Methode
Abstract	This book presents a thorough treatment and unified coverage of Bayesian item response modeling with applications in a variety of disciplines, including education, medicine, psychology, and sociology. Breakthroughs in computing technology have made the Bayesian approach particularly useful for many response modeling problems. Free from computational constraints, realistic and state-of-the-art latent variable response models are considered for complex assessment and survey data to solve real-world problems. The Bayesian framework described provides a unified approach for modeling and inference, dealing with (nondata) prior information and information across multiple data sources. The book discusses methods for analyzing item response data and the complex relationships commonly associated with human response behavior and features: 1. Self-contained introduction to Bayesian item response modeling and a coverage of extending standard models to handle complex assessment data; 2. A thorough overview of Bayesian estimation and testing methods for item response models, where MCMC methods are emphasized; 3. Numerous examples that cover a wide range of application areas, including education, medicine, psychology, and sociology. (DIPF/Orig.).
Erfasst von	DIPF \| Leibniz-Institut für Bildungsforschung und Bildungsinformation, Frankfurt am Main
Update	2011/1