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Introduction to the Rasch model with examples in R

By: Contributor(s): Series: Chapman & Hall/CRC Statistics in the Social and Behavioral SciencesPublication details: Chapman and Hall/CRC 2022 Boca RatonDescription: 306pISBN:
  • 9781138710467
Subject(s): DDC classification:
  • 519.5 DEB
Summary: 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. This 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. 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.
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Item type Current library Collection Call number Status Date due Barcode Item holds
Book Book Jammu General Stacks Non-fiction 150.287 DEB (Browse shelf(Opens below)) Available IIMJ-7117
Total holds: 0

Table of Contents: 1. The Rasch model 2. Parameter estimation 3. Test evaluation 4. Basic R usage 5. R package eRm 6. R package mirt 7. R package TAM 8. R interface to Stan 9. Extensions to the Rasch model 10. Models for polytomous responses 11. 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. This 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. 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.

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