Currently there are many introductory textbooks on educational measurement and psychometrics as well as R. However, there is no single book that covers important topics in measurement and psychometrics as well as their applications in R.
The Handbook of Educational Measurement and Psychometrics Using R covers a variety of topics, including classical test theory; generalizability theory; the factor analytic approach in measurement; unidimensional, multidimensional, and explanatory item response modeling; test equating; visualizing measurement models; measurement invariance; and differential item functioning.
This handbook is intended for undergraduate and graduate students, researchers, and practitioners as a complementary book to a theory-based introductory or advanced textbook in measurement. Practitioners and researchers who are familiar with the measurement models but need to refresh their memory and learn how to apply the measurement models in R, would find this handbook quite fulfilling. Students taking a course on measurement and psychometrics will find this handbook helpful in applying the methods they are learning in class. In addition, instructors teaching educational measurement and psychometrics will find our handbook as a useful supplement for their course.
"This book provides excellent coverage of conducting psychometric analyses using R for all levels, including psychometricians, researchers, and graduate students. The book would also serve as a top-notch companion to a theoretical measurement/psychometric textbook. The book uses a hands-on approach with explanation through practical examples that provide readers with commentary about the input and output for each analysis covered. The R code provided in the examples will be helpful for both seasoned and new users of R. Overall, this book combines readability, practical examples, and many pieces of R code into a superb resource to aid in conducting psychometric analyses."
—Brandon LeBeau, Assistant Professor, University of Iowa
"The Handbook of Educational Measurement and Psychometrics Using R is an outstanding addition to literature. The content is both broad and comprehensive thereby providing researchers and practitioners alike with an excellent resource for dealing with a diverse range of psychometric analyses. Also, instructors could use the Handbook as a complimentary text for teaching introductory and advanced measurement courses because programming with R eliminates the need to use different software programs. In short, the Handbook is a very useful and much needed resource for our field."
—Dr. Mark Gierl, Professor of Educational Psychology, Canada Research Chair in Educational Measurement, Director, Centre for Research in Applied Measurement and Evaluation, University of Alberta, Edmonton, Alberta, Canada
"This book may be the first attempt to demonstrate how to use R to analyze data in the fields of educational measurement and psychometrics. The rapid development of R has also facilitated the implementation of some data analyses which were conducted using costly software in the past. One of the unique features of this textbook is that it illustrates step by step how to analyze data focusing on educational measurement and psychometric methods. Such a detailed approach makes it an extremely useful textbook for learning. It is a must for my graduate-level educational measurement and psychometrics courses. Moreover, this book is a great resource when I am analyzing data using R in my own research. In sum, this book is highly recommended for anyone wishing to teach a measurement course using R and to advance their own research based on psychometric methods."
—Pey-Yan Liou, Graduate Institute of Learning and Instruction, National Central University
Introduction to the R Programming Language
Classical Test Theory
Factor Analytic Approach in Measurement
Item Response Theory for Dichotomous Items
Item Response Theory for Polytomous Items
Multidimensional Item Response Theory
Explanatory Item Response Theory
Visualizing Data and Measurement Models
Measurement Invariance and Differential Item Functioning
More Advanced Topics in Measurement