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Item Response Theory clearly describes the most recently developed IRT models and furnishes detailed explanations of algorithms that can be used to estimate the item or ability parameters under various IRT models. Extensively revised and expanded, this edition offers three new chapters discussing parameter estimation with multiple groups, parameter estimation for a test with mixed item types, and Markov chain Monte Carlo methods. It includes discussions on issues related to statistical theory, numerical methods, and the mechanics of computer programs for parameter estimation, which help to build a clear understanding of the computational demands and challenges of IRT estimation procedures.
- Sales Rank: #1251178 in Books
- Brand: Brand: CRC Press
- Published on: 2004-07-20
- Original language: English
- Number of items: 1
- Dimensions: 9.21" h x 1.13" w x 6.14" l, 1.85 pounds
- Binding: Hardcover
- 528 pages
- Used Book in Good Condition
Most helpful customer reviews
0 of 0 people found the following review helpful.
Rasch versus IRT models, theoretical underpinnings, and consequent practices
By Cilio Ziviani
The book is a thorough review of parameter estimation in most important item response theory models. For me, the outstanding part is the one that clearly distinguish the Rasch family from the IRT many other models.
6 of 7 people found the following review helpful.
Great resource but leaves a gap for applicability
By J. Humphries
This text does an excellent job of tying IRT theories together and explaining the underlying premises for this important realm of testing and assessment. However, I was seeking a book less burried in theories and more of a how-to manual. This text establishes a foundation for someone to understand how to apply IRT but does not offer a quick and easy to use reference for a practitioner seeking to consider the nuances of preferable approaches to test development and scoring.
2 of 3 people found the following review helpful.
awesome
By Amazon Customer
This is book is awesome at explaining the IRT model in plain English. It it not full of esoteric jargon, and it allows the reader to clearly grasp the fundamentals of IRT.
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