Description
“A Course in Rasch Measurement Theory” is a comprehensive guide to understanding Rasch measurement theory, written in a clear and accessible style for both beginners and experts alike. Authored by [insert author name], this book serves as an essential resource for anyone interested in measurement theory, educational assessment, or social science research.
Rasch measurement theory, named after Danish mathematician Georg Rasch, provides a powerful framework for developing valid and reliable measurement instruments. Unlike traditional psychometric approaches, which focus on statistical methods for analyzing test data, Rasch measurement theory emphasizes the fundamental principles of measurement itself.
At the heart of Rasch measurement theory is the concept of the Rasch model, which posits that the probability of a respondent endorsing an item on a scale depends solely on the relationship between the respondent’s ability and the difficulty of the item. This simple yet elegant model forms the basis for a wide range of measurement applications, from educational testing to health outcomes assessment.
The book begins with an introduction to the basic principles of Rasch measurement theory, including an overview of the Rasch model and its key assumptions. It then provides step-by-step guidance on how to apply Rasch analysis to real-world data, covering topics such as item calibration, person measurement, and test equating.
One of the strengths of “A Course in Rasch Measurement Theory” is its emphasis on practical applications. The author illustrates key concepts with concrete examples drawn from various fields, including education, psychology, and healthcare. This hands-on approach not only helps readers understand the theory but also equips them with the skills they need to apply it in their own research or practice.
In addition to covering the core principles of Rasch measurement theory, the book also explores advanced topics such as differential item functioning (DIF), multidimensional Rasch models, and item response theory (IRT). These topics are presented in a clear and accessible manner, making them accessible to readers with varying levels of statistical expertise.
Throughout the book, the author provides helpful tips and guidance for conducting Rasch analysis using popular software packages such as RUMM, Winsteps, and jMetrik. This practical advice is invaluable for researchers who are new to Rasch analysis or who may be struggling with complex data sets.
Overall, “A Course in Rasch Measurement Theory” is an indispensable resource for researchers, educators, and practitioners seeking to deepen their understanding of measurement theory and enhance the quality of their measurement instruments. With its clear explanations, practical examples, and expert guidance, this book is sure to become a trusted companion for anyone working in the field of measurement science.
