Автор: Iasonas Lamprianou
Издательство: Routledge
Год: 2025
Страниц: 321
Язык: английский
Формат: pdf (true), epub
Размер: 20.5 MB
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 (“latent”) 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.
There is a lot of freely accessible material on the internet regarding the basic mechanics of using the R platform. Most of this material is of very good quality and is easy to read and understand. It is also possible to find tons of very useful introductory material regarding R on YouTube. There are also many recent and well-written books on R; you can search them on the internet or through your favorite bookseller (e.g., search for “R package” at Amazon). Using these resources, videos, and books, will give you a very good idea about how to download, install, and run R.
R is a very rich environment which can be used for data processing and statistical analysis but can also be used as an ordinary programming language. Thus, how you use R is practically limited only by your imagination. Having prior experience with programming is not necessary, but it is always helpful.
Most of the commands needed for this book will be provided to the reader and may be executed either on R console or through the point-and-click environment of BlueSky Statistics. A lot of information is freely available to instruct the user how to download, install and run the BlueSky Statistics software. There is also a rich gallery of short and succinct videos, which can be freely accessed by anyone. BlueSky Statistics is an application customized to use R’s great power. It has a very user-friendly environment and provides all the functionality needed for this book. Our primary aim is to guide the reader to run all models on R console. However, for those who prefer the point-and-click environment, BlueSky Statistics is a great option.
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