Computational Aspects of Psychometric Methods
Product details
- ISBN 9780367515393
- Weight: 720g
- Dimensions: 178 x 254mm
- Publication Date: 03 Jul 2023
- Publisher: Taylor & Francis Ltd
- Publication City/Country: GB
- Product Form: Paperback
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This book covers the computational aspects of psychometric methods involved in developing measurement instruments and analyzing measurement data in social sciences. It covers the main topics of psychometrics such as validity, reliability, item analysis, item response theory models, and computerized adaptive testing. The computational aspects comprise the statistical theory and models, comparison of estimation methods and algorithms, as well as an implementation with practical data examples in R and also in an interactive ShinyItemAnalysis application.
Key Features:
- Statistical models and estimation methods involved in psychometric research
- Includes reproducible R code and examples with real datasets
- Interactive implementation in ShinyItemAnalysis application
The book is targeted toward a wide range of researchers in the field of educational, psychological, and health-related measurements. It is also intended for those developing measurement instruments and for those collecting and analyzing data from behavioral measurements, who are searching for a deeper understanding of underlying models and further development of their analytical skills. The datasets and the R code can be accessed here: https://www.cs.cas.cz/comps/CAPMbook/.
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.
