Description

Book Synopsis

This new edition provides a step-by-step guide to applying the Rasch model in R, a probabilistic model used by researchers across the social sciences to measure unobservable (âœlatentâ) variables. Although the focus is on simple R code, the book provides updated guidance through the point-and-click menus of BlueSky Statistics software.

The book covers all Rasch models frequently used in social sciences, from the Simple Rasch model to the Rating Scale, Partial Credit, and Many-Facets Rasch models. Using a pragmatic approach to model-data fit, this book offers helpful practical examples to investigate Rasch model assumptions. In addition to traditional Rasch model approaches, it introduces the Rasch model as a special case of a Generalized Mixed Effects Model. Readers will also benefit from the online support material which includes all the code used in the book in downloadable and useable files.

It also provides a comprehensive guide to R programming and practical guidance on using BlueSky Statistics software's point-and-click menus. This dual approach enables readers to experiment with data analysis using the provided data sets, enhancing their understanding and application of statistical concepts. It will be a valuable resource for both students and researchers who want to use Rasch models in their research.

A StepbyStep Guide to Applying the Rasch Model

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    A Paperback by Iasonas Lamprianou

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      View other formats and editions of A StepbyStep Guide to Applying the Rasch Model by Iasonas Lamprianou

      Publisher: Taylor & Francis
      Publication Date: 12/17/2024
      ISBN13: 9781032619408, 978-1032619408
      ISBN10: 1032619406

      Description

      Book Synopsis

      This new edition provides a step-by-step guide to applying the Rasch model in R, a probabilistic model used by researchers across the social sciences to measure unobservable (âœlatentâ) variables. Although the focus is on simple R code, the book provides updated guidance through the point-and-click menus of BlueSky Statistics software.

      The book covers all Rasch models frequently used in social sciences, from the Simple Rasch model to the Rating Scale, Partial Credit, and Many-Facets Rasch models. Using a pragmatic approach to model-data fit, this book offers helpful practical examples to investigate Rasch model assumptions. In addition to traditional Rasch model approaches, it introduces the Rasch model as a special case of a Generalized Mixed Effects Model. Readers will also benefit from the online support material which includes all the code used in the book in downloadable and useable files.

      It also provides a comprehensive guide to R programming and practical guidance on using BlueSky Statistics software's point-and-click menus. This dual approach enables readers to experiment with data analysis using the provided data sets, enhancing their understanding and application of statistical concepts. It will be a valuable resource for both students and researchers who want to use Rasch models in their research.

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