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Handbook of Item Response Theory

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3PL Model
Ability Parameters
advanced item response theory models
Age Group_Uncategorized
Age Group_Uncategorized
automatic-update
B01=Wim J. van der Linden
Bifactor Model
Category Response Functions
Category1=Non-Fiction
Category=JMBT
COP=United States
Delivery_Delivery within 10-20 working days
educational measurement
eq_bestseller
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
generalized models
GPC Model
Graded Response Model
hierarchical response models
IRT
IRT Model
Item Difficulties
Item Parameter
Item Response Models
Joint Maximum Likelihood Estimation
Language_English
Latent Traits
latent variable modeling
Maximum Marginal Likelihood Computations
Maximum Marginal Likelihood Estimation
Mixture IRT
Mixture IRT Model
model parameter
models in IRT
multidimensional models
Normal Ogive Model
PA=Available
Partial Credit Model
Pi Pi
Pi Pi Pi
Posterior Distributions
Price_€100 and above
PS=Active
psychometrics
Rasch's Model
Rasch’s Model
response modeling
response time modeling
softlaunch
statistical estimation methods
test data analysis
Test Takers
test theory
Von Davier

Product details

  • ISBN 9781466514317
  • Weight: 1300g
  • Dimensions: 178 x 254mm
  • Publication Date: 15 Aug 2016
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
  • Language: English
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Description

Drawing on the work of internationally acclaimed experts in the field, Handbook of Item Response Theory, Volume One: Models presents all major item response models. This first volume in a three-volume set covers many model developments that have occurred in item response theory (IRT) during the last 20 years. It describes models for different response formats or response processes, the need of deeper parameterization due to a multilevel or hierarchical structure of the response data, and other extensions and insights.

In Volume One, all chapters have a common format with each chapter focusing on one family of models or modeling approach. An introductory section in every chapter includes some history of the model and a motivation of its relevance. Subsequent sections present the model more formally, treat the estimation of its parameters, show how to evaluate its fit to empirical data, illustrate the use of the model through an empirical example, and discuss further applications and remaining research issues.
About

Wim J. van der Linden is a distinguished scientist and director of research innovation at Pacific Metrics Corporation. He is also a professor emeritus of measurement and data analysis at the University of Twente. He is a past president of the Psychometric Society and National Council on Measurement in Education (NCME) and a recipient of career achievement awards from NCME, Association of Test Publishers (ATP), and American Educational Research Association (AERA). His research interests include test theory, computerized adaptive testing, optimal test assembly, parameter linking, test equating, and response-time modeling as well as decision theory and its application to problems of educational decision making. Dr. van der Linden earned a PhD in psychometrics from the University of Amsterdam.