Item Response Theory: Parameter Estimation Techniques, Second Edition

Item Response Theory (IRT) is a statistical framework that estimates item or ability parameters under various models. This edition provides detailed explanations of algorithms and discusses parameter estimation with multiple groups, mixed item types, and Markov chain Monte Carlo methods. It also addresses statistical theory, numerical methods, and computational challenges, aiding in understanding the computational demands and complexities of IRT estimation procedures.

Format: Paperback / softback
Length: 524 pages
Publication date: 21 January 2023
Publisher: Taylor & Francis Ltd

Item Response Theory (IRT) is a powerful tool for assessing the performance of individuals on a variety of tasks. It provides a comprehensive framework for understanding how individuals respond to different items or stimuli and how these responses can be used to measure their abilities or competencies.

IRT models are based on the assumption that the relationship between an individual's response to an item and their underlying ability or trait is linear. This means that a change in the item's difficulty or discrimination power will result in a corresponding change in the individual's score.

There are several different types of IRT models, including the Rasch model, the polytomous item response theory (MIRT) model, and the generalized linear model (GLM) model. Each of these models has its own unique strengths and weaknesses, and they are often used in combination to provide a more comprehensive assessment of an individual's abilities.

One of the key advantages of IRT is that it provides detailed explanations of the algorithms that can be used to estimate the item or ability parameters under various IRT models. These algorithms are based on statistical principles and can be used to analyze large datasets of test scores and other relevant information.

In recent years, IRT has been extensively revised and expanded, with three new chapters discussing parameter estimation with multiple groups, parameter estimation for a test with mixed item types, and Markov chain Monte Carlo methods. These chapters provide a comprehensive overview of the latest developments in IRT and help to build a clear understanding of the computational demands and challenges of IRT estimation procedures.

In addition to its theoretical foundations, IRT has practical applications in a wide range of fields, including education, psychology, and healthcare. For example, it can be used to develop and validate assessment instruments, such as tests and surveys, that measure a variety of skills and competencies. It can also be used to analyze data from existing assessments to identify areas where individuals may need additional support or intervention.

Overall, Item Response Theory is a powerful tool for assessing the performance of individuals on a variety of tasks. It provides a comprehensive framework for understanding how individuals respond to different items or stimuli and how these responses can be used to measure their abilities or competencies. With its extensive revisions and expansions, IRT continues to be an important tool for researchers and practitioners in a wide range of fields.

Weight: 970g
Dimension: 234 x 156 (mm)
ISBN-13: 9781032477923
Edition number: 2 ed