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Rasch Measurement Theory Analysis in R
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Rasch Measurement Theory Analysis in R

Book Details

Format Hardback or Cased Book
ISBN-10 1032005602
ISBN-13 9781032005607
Publisher Taylor & Francis Ltd
Imprint Chapman & Hall/CRC
Country of Manufacture GB
Country of Publication GB
Publication Date Jun 3rd, 2022
Print length 316 Pages
Weight 640 grams
Ksh 30,600.00
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Provides researchers & practitioners with a step-by-step guide for conducting Rasch measurement theory analyses. 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.

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.


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