Advances in Rasch Analyses in the Human Sciences

This volume follows the publication of Rasch Analysis in the Human Sciences. This new book presents additional topics not discussed in the previous volume. It examines key topics such as partial credit analysis of data, common person linking, computing equating constants, investigating discrimination, evaluating dimensionality, how to better utilize Wright Maps, how to design tests and surveys using Rasch theory, and many more. The book includes activities which can be used to practice the theme of each chapter and to test the reader’s understanding of Rasch techniques. Beginning and ending with a conversation between two students, each chapter provides clear step-by-step instructions as to how to conduct an analysis using the chapter theme. The chapters emphasize applications for the beginner learning Rasch and provide guidance for composing a write-up of an analysis for a presentation, paper, thesis or report.

This book explores in detail many important yet often rarely discussed topics in Rasch. With its easy-to-read language and engaging format it reaches a wide audience of scientists, clinicians, students, researchers and psychometricians, providing a valuable toolkit for practical users of Rasch analysis. – Dr. Eva Fenwick, Clinical Research Fellow, Singapore Eye Research Institute (SERI) Assistant Professor, Duke-NUS Medical School, Singapore

It is an easy to read book and provides immediate guidance for those wishing to conduct a Rasch analysis. The “conversations” between students in each chapter provides a welcome introduction to each topic. – Prof. Maik Walpuski, University Duisburg-Essen, Germany

The lessons learned in their first book are extended by providing insightful demonstrations of some of the more complex concepts and techniques used in applying Rasch models. – Dr. Michael R. Peabody, National Association of Boards of Pharmacy, Illinois, USA

I am amazed with the ability of these authors to communicate complicated knowledge, and the ability to mak