Item Response Theory: Parameter Estimation Techniques, Second Edition

ISBN-13: 9781032477923 / Angielski / Miękka / 2023 / 524 str.

Frank B. Baker; Seock-Ho Kim

Opis

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.

Recenzje

"…an excellent resource for the serious investigator doing research involving estimation of IRT model parameters."
-Journal of the American Statistical Association

"…Baker has the unique ability to present complex material in a form that is easily understood….This book belongs on the bookshelf of every advanced student in psychometrics. It should also prove invaluable to students in statistics."
-Journal of Educational Measurement

Spis treści

The Item Characteristic Curve: Dichotomous Response. Estimating the Parameters of an Item Characteristic Curve. Maximum Likelihood Estimation of Examinee Ability. Maximum Likelihood Procedures for Estimating Both Ability and Item Parameters. The Rasch Model. Marginal Maximum Likelihood Estimation and an EM Algorithm. Bayesian Parameter Estimation Procedures. The Graded Item Response. Nominally Scored Items. Markov Chain Monte Carlo Methods. Parameter Estimation with Multiple Groups. Parameter Estimation for a Test with Mixed Item Types

O autorze

Frank B. Baker, Seock-Ho Kim