Using R for item response theory model applicationsКНИГИ » ПРОГРАММИНГ
Название: Using R for item response theory model applications Автор: Insu Paek, Ki Cole Издательство: Routledge Год: 2020 Страниц: 280 Язык: английский Формат: pdf (true), djvu Размер: 10.1 MB
Item response theory (IRT) is widely used in education and psychology and is expanding its applications to other social science areas, medical research, and business as well. Using R for Item Response Theory Model Applications is a practical guide for students, instructors, practitioners, and applied researchers who want to learn how to properly use R IRT packages to perform IRT model calibrations with their own data.
In recent years, the open-source statistical computing and programming language R has become very popular. Furthermore, IRT programs, known as packages, have been introduced in the R environment. The R software and its corresponding programs are free. Because of its open-source nature, the details of the programs, including source codes and package documentations, are openly available. Many have learned R through trial and error using the provided R program documentation, but this may be a particularly time-consuming experience depending on the extent of the documentation, the programs’ complexities, and possibly the learner’s background. This book was written to help minimize this inefficient process and laborious experience of those beginners who want to learn how to use R for IRT analysis. And in the process, readers may learn and understand additional features of the R IRT programs that they may not have discovered on their own.
This book provides practical line-by-line descriptions of how to use R IRT packages for various IRT models. The scope and coverage of the modeling in the book covers almost all models used in practice and in popular research, including:
dichotomous response modeling polytomous response modeling mixed format data modeling concurrent multiple group modeling fixed item parameter calibration modelling with latent regression to include person-level covariate(s) simple structure, or between-item, multidimensional modeling cross-loading, or within-item, multidimensional modeling high-dimensional modeling bifactor modeling testlet modeling two-tier modeling
For beginners, this book provides a straightforward guide to learn how to use R for IRT applications. For more intermediate learners of IRT or users of R, this book will serve as a great time-saving tool for learning how to create the proper syntax, fit the various models, evaluate the models, and interpret the output using popular R IRT packages.
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Geocomputation with R Название: Geocomputation with R Автор: Robin Lovelace, Jakub Nowosad, Jannes Muenchow Издательство: Chapman and Hall/CRC Серия: The R Series Год:...
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Using R for item response theory model applications 
