Patrícia Martinková is a Senior Researcher at the Institute of Computer Science of the Czech Academy of Sciences and an Academic Researcher at Charles University. Her research spans psychometrics and statistics with a focus on mathematical, statistical, and computational aspects of measurement. She has been teaching courses on psychometric methods since 2014. Adéla Hladká is a Postdoctoral Fellow at the Institute of Computer Science of the Czech Academy of Sciences. Her research interests include psychometrics and statistics, with a focus on differential item functioning, and software development with R.
"""This book is an excellent combination of introductory and recent advanced psychometric developments with implemented and illustrated examples using R. The book is clearly written and covers man different topics but is especially interesting as R code are given so the reader can learn how to perform the described analyses. Several datasets are given, and the examples are well explained to help readers to learn the methods. The methods in the book include, but are not limited to classical test theory, item response theory (IRT), item analysis, and differential item functioning. I highly recommend this book, both as course book when teaching psychometrics but also for researchers who wants to perform advanced analyses."" - Marie Wiberg, Professor, Umeå University ""This book is both a comprehensive introduction to psychometrics and a practical guide to implement the methods using R. It covers a wide range of topics, always providing real-case applications and the R code needed to analyse the data. Remarkable strengths of the book are the large variety of datasets used as examples and the fine balance between theory and applications. The book is suitable as a textbook for Psychometrics courses, and it can be of interest to researchers as well."" - Michela Battauz, Associate Professor, University of Udine. ""I have been instructionally using the R package ShinyItemAnalysis, written by the lead author and her team, for several years and am pleased to see this book appear. It is written in a manner that is clear and inviting to the reader and the mathematics necessary to understand the text is mostly within the reach of someone who has taken introductory statistics, regression, and categorical data. Similarly, the necessary R is also kept fairly basic. In addition to item response theory (IRT), the text contains content on topics such as regression-based item analysis, item bias, classical test theory, and computerized adaptive testing. As such, it would be an excellent addition to an IRT course using R. An instructor using a different text but needing examples and exercises in R would also benefit, as would a motivated scholar undertaking self-study. In sum, I highly recommend this book."" - Jay Verkuilen, Associate Professor, The City University of New York."