Bayesian Item Response Modeling
“Bayesian Item Response Modeling: Theory and Applications” is published by Springer in the series Statistics for Social and Behavioral Sciences (June 2010). There is also a product flyer from Springer. ( (product flyer)
This book presents a thorough treatment and unified coverage of Bayesian item response modeling with applications in a variety of disciplines, including education, medicine, psychology, and sociology. Breakthroughs in computing technology have made the Bayesian approach particularly useful for many response modeling problems. Free from computational constraints, realistic and state-of-the-art latent variable response models are considered for complex assessment and survey data to solve real-world problems.
The Bayesian framework described provides a unified approach for modeling and inference, dealing with prior information and information across multiple data sources. The book discusses methods for analyzing item response data and the complex relationships commonly associated with human response behavior.
Self-contained introduction to Bayesian item response modeling and a coverage of extending standard models to handle complex assessment data. Gives a thorough overview of Bayesian estimation and testing methods for item response models, where MCMC methods are emphasized. Contains numerous examples that cover a wide range of application areas, including education, medicine, psychology, and sociology.
Data and software (under tab Software).