ability
Ability Estimate
Ability Parameters
advanced item response modeling applications
Bayesian inference methods
Category=JMB
Category=PBT
characteristic
Cumulative Distribution Function
curve
Driver Section
educational measurement theory
eq_bestseller
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
equation
estimates
estimation
Gibbs Sampler
Graded Response Model
ICC Model
Initialization Subroutine
IRT Model
Item Characteristic Curve
Item Characteristic Curve Model
Item Information Function
Item Parameter
Item Parameter Estimation
Item Response Category
Item Response Theory
latent trait analysis
Logistic Ogive
Marginal Maximum Likelihood Estimation
Maximum Likelihood Estimation Process
newton
Newton Raphson Equation
Newton Raphson Procedure
Normal Ogive
Normal Ogive Model
parameter
parameters
psychometric modeling
Quadrature Nodes
raphson
Rasch Model
statistical computation
test validation techniques
Product details
- ISBN 9781032477923
- Weight: 780g
- Dimensions: 156 x 234mm
- Publication Date: 21 Jan 2023
- Publisher: Taylor & Francis Ltd
- Publication City/Country: GB
- Product Form: Paperback
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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.
