Rasch Measurement Theory Analysis in R
- Length: 316 pages
- Edition: 1
- Language: English
- Publisher: Chapman & Hall
- Publication Date: 2022-06-03
- ISBN-10: 0367776391
- ISBN-13: 9780367776398
- Sales Rank: #0 (See Top 100 Books)
Rasch Measurement Theory Analysis in R provides researchers and practitioners with a step-by-step guide for conducting Rasch measurement theory analyses using R. It includes theoretical introductions to major Rasch measurement principles and techniques, demonstrations of analyses using several R packages that contain Rasch measurement functions, and sample interpretations of results.
Features:
Accessible to users with relatively little experience with R programming Reproducible data analysis examples that can be modified to accommodate users’ own data Accompanying e-book website with links to additional resources and R code updates as needed Features dichotomous and polytomous (rating scale) Rasch models that can be applied to data from a wide range of disciplines This book is designed for graduate students, researchers, and practitioners across the social, health, and behavioral sciences who have a basic familiarity with Rasch measurement theory and with R. Readers will learn how to use existing R packages to conduct a variety of analyses related to Rasch measurement theory, including evaluating data for adherence to measurement requirements, applying the dichotomous, Rating Scale, Partial Credit, and Many-Facet Rasch models, examining data for evidence of differential item functioning, and considering potential interpretations of results from such analyses.
Cover Half Title Series Page Title Page Copyright Page Contents 1. Introduction 1.1. Overview of Rasch Measurement Theory 1.2. Online Resources 2. Dichotomous Rasch Model 2.1. Example Data: Transitive Reasoning Test 2.2. Dichotomous Rasch Model Analysis with CMLE in eRm 2.3. Dichotomous Rasch Model Analysis with MMLE in TAM 2.4. Dichotomous Rasch Model Analysis with JMLE in TAM 2.5. Example Results Section 2.6. Exercise 2.7. Supplementary Learning Materials 3. Evaluating the Quality of Measures 3.1. Evaluating Measurement Quality from the Perspective of Rasch Measurement Theory 3.2. Example Data: Transitive Reasoning Test 3.3. Rasch Model Fit Analysis with CMLE in eRm 3.4. Graphical Displays for Evaluating Model-Data Fit 3.5. Rasch Model Fit Analysis with MMLE in TAM 3.6. Rasch Model Fit Analysis with JMLE in TAM 3.7. Exercise 4. Rating Scale Model 4.1. Example Data: Liking for Science 4.2. RSM Analysis with CMLE in eRm 4.3. RSM Analysis with MMLE in TAM 4.4. RSM Analysis with JMLE in TAM 4.5. Example Results Section 4.6. Exercise 5. Partial Credit Model 5.1. Example Data: Liking for Science 5.2. PCM Analysis with CMLE in eRm 5.3. Summarize the Results in Tables 5.4. PCM Application with MMLE in TAM 5.5. PCM Application with JMLE in TAM 5.6. Example Results Section 5.7. Exercise 6. Many Facet Rasch Model 6.1. Running the MFRM with Wide-Format Data in TAM Package 6.2. Another Example: Running PC-MFRM with Long-Format Data using the TAM Package 6.3. Notes on Formulations for Many-Facet Rasch Models 6.4. Example Results Section 6.5. Exercise 7. Basics of Differential Item Functioning 7.1. Detecting Differential Item Functioning in R for Dichotomous Items 7.2. Detecting Differential Item Functioning in R for Polytomous Items 7.3. Exercise Bibliography Index
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