Back to results
Cover image for book Multivariate and Mixture Distribution Rasch Models

Multivariate and Mixture Distribution Rasch Models

Extensions and Applications
By:Matthias Davier; Claus H. Carstensen
Publisher:Springer Nature
Print ISBN:9780387329161
eText ISBN:9780387498393
Edition:0
Copyright:2007
Format:Page Fidelity

eBook Features

Instant Access

Purchase and read your book immediately

Read Offline

Access your eTextbook anytime and anywhere

Study Tools

Built-in study tools like highlights and more

Read Aloud

Listen and follow along as Bookshelf reads to you

This volume gathers together a set of extensions of the Rasch model, one of the most prominent models for measurement in educational research and - cial science developed by Danish mathematician Georg Rasch. The idea for this volume emerged during a meeting of the Psychometric Society in M- terey, CA. At that meeting, friends and colleagues discussed news about the impending retirement of Dr. Jurgen ¨ Rost, an important innovator and m- tor in this ?eld. To recognize Jurgen’s ¨ contributions, we decided to produce a collection of research on extending the Rasch model as well as embedding the Rasch model in more complex statistical models, an area that is receiving broad interest in many ?elds of social sciences at the current time. This collection contains 22 chapters by recognized international experts in the?eld.Thecontributionscovertopicsrangingfromgeneralmodelextensions to application in ?elds as diverse as cognition, personality, organizational and sports psychology, and health sciences and education. The Rasch model is designed for categorical data, often collected as ex- inees’ responses to multiple tasks such as cognitive items from psychological tests or from educational assessments. The Rasch model’s elegant mathema- cal form is suitable for extensions that allow for greater ?exibility in handling complex samples of examinees and collections of tasks from di?erent domains. In these extensions, the Rasch model is enhanced by additional structural - ements that account either for di?erences between diverse populations or for di?erences among observed variables.