An introduction to the Rasch model with examples in R / Rudolf Debelak, Carolin Strobl and Matthew D. Zeigenfuse.
Material type:
- text
- unmediated
- volume
- 9781032265582
- 9781138710467
- 150.28/7 23 Ed.
- BF39.2.I84 D43 2022
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RLKU Library & Information Resource Center | 005 DEB (Browse shelf(Opens below)) | Available | 12796 | |
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RLKU Library & Information Resource Center | 005 DEB (Browse shelf(Opens below)) | Available | 12797 | |
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RLKU Library & Information Resource Center | 005 DEB (Browse shelf(Opens below)) | Available | 12798 | |
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RLKU Library & Information Resource Center | 005 DEB (Browse shelf(Opens below)) | Available | 12799 | |
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RLKU Library & Information Resource Center | 005 DEB (Browse shelf(Opens below)) | Available | 12800 |
Includes bibliographical references and index.
The Rasch model -- Parameter estimation -- Test evaluation -- Basic R usage -- R package eRm -- R package mirt -- R package TAM -- R interface to Stan -- Extensions to the Rasch model -- Models for polytomous responses -- Outlook on special applications.
"This book offers a clear, comprehensive introduction to the Rasch model along with practical examples in the free, open-source software R. It is accessible for readers without a background in psychometrics or statistics, while also providing detailed explanations of the relevant mathematical and statistical concepts for readers who want to gain a deeper understanding. Its worked examples in R demonstrate how to apply the methods to real-world examples and how to interpret the resulting output. In addition to motivating and presenting the Rasch model, the book covers different methods for parameter estimation and for assessing fit and differential item functioning (DIF). While focusing on the Rasch model, it also addresses a variety of other dichotomous and polytomous Rasch and item response theory (IRT) models, such as two-parameter logistic (2PL) and Partial Credit models, and extensions, including mixture Rasch models and computerized adaptive testing (CAT). Theory is presented in a self-contained way. All necessary mathematical and statistical background is contained in the chapters and appendices. The book also provides detailed, step-by-step instructions for getting started with R and using the eRm, mirt, TAM and rstan packages for fitting Rasch models"-- Provided by publisher.
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