Description
Book SynopsisThe modeling of item response data is governed by item response theory, also referred to as modern test theory. The usefulness of the Bayesian methodology is illustrated by discussing and applying a range of Bayesian item response models.
Trade ReviewFrom the reviews:
“Item response theory is a general paradigm for the design and analysis of questionnaires measuring abilities and attitudes of individuals. … the book is written in a concise style and the technical level of the book is relatively high. … I believe this book makes an important contribution in summarizing much of the important literature in Bayesian IRT and I think it will lead to future books focusing on the use and interpretation of these models from a practitioner’s perspective.” (Jim Albert, Journal of the American Statistical Association, Vol. 106 (495), September, 2011)
“This book covers the parameter estimation of standard and extended IRT models using the Bayesian simulation based MCMC method. There are many Bayesian data analysis books, but this is the first book purely devoted to the Bayesian estimation of IRT models. … Overall, it is a good book for advanced learners to grasp the theoretical and technical detail of Bayesian MCMC estimation of extended IRT models adapted to a specific measurement setting.” (Hong Jiao, Psychometrika, Vol. 76 (2), April, 2011)
“This book develops a comprehensive treatment of Bayesian item response modelling … . The book is mostly self-contained. … Each chapter ends with a section of carefully thought-out exercises covering both the mathematical aspects of the models and their application to the analysis of interesting real-life data. … This book will equally cater for those users who just want to apply the models to analyze their data, and more technical users willing to get a deeper understanding of the models … .” (Eduardo Gutiérrez-Peña, International Statistical Review, Vol. 79 (3), 2011)
Table of Contentsto Bayesian Response Modeling.- Bayesian Hierarchical Response Modeling.- Basic Elements of Bayesian Statistics.- Estimation of Bayesian Item Response Models.- Assessment of Bayesian Item Response Models.- Multilevel Item Response Theory Models.- Random Item Effects Models.- Response Time Item Response Models.- Randomized Item Response Models.
