Multidimensional Item Response Theory
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Оглавление
Wes Bonifay. Multidimensional Item Response Theory
Quantitative Applications in the Social Sciences
Multidimensional Item Response Theory
Contents
Series Editor’s Introduction
Acknowledgments
About the Author
Chapter 1 Introduction
Chapter 2 Unidimensional Item Response Theory
What Is a Latent Trait?
Assumptions of UIRT
UIRT Models for Dichotomous Data
R Code
UIRT Models for Polytomous Data
Difference Models
Divide-by-Total Models
Additional UIRT Models
R Code
UIRT Estimation
Joint Estimation of Both Person and Item Parameters
The EM Algorithm
Scoring
Other Estimation Methods
R Code
Descriptions of Images and Figures
Chapter 3 MIRT Models for Dichotomous Data
Compensation in MIRT Modeling
Compensatory MIRT Models
R Code
Partially Compensatory MIRT Models
R Code
Additional MIRT Models for Dichotomous Data
R Code
Recent Advances in Dichotomous MIRT Modeling
Descriptions of Images and Figures
Chapter 4 MIRT Models for Polytomous Data
R Code
Additional Polytomous MIRT Models
Descriptions of Images and Figures
Chapter 5 Descriptive MIRT Statistics
The θ-Space
The Item Response Surface
Conditional Response Functions
The Direction of Measurement
Person Parameters in MIRT
MIRT Information
Polytomous MIRT Descriptives
Test-Level MIRT Descriptives
Descriptions of Images and Figures
Chapter 6 Item Factor Structures
Two-Tier Model
Correlated-Traits Model
Bifactor Model
Testlet Response Model
R Code
Descriptions of Images and Figures
Chapter 7 Estimation in MIRT Models
Conceptual Illustration
Missing Data Formulation
Two Challenges
Adaptive Quadrature
Bayesian Estimation
MH-RM Estimation
R Code
Descriptions of Images and Figures
Chapter 8 MIRT Model Diagnostics and Evaluation
Dimensionality Assessment
Test-Level Fit Assessment
Item-Level Fit Assessment
Model Comparison Methods
Chapter 9 MIRT Applications
Linking and Equating
R Code
Differential Item Functioning
R Code
Computerized Adaptive Testing
R Code
Applications of the Two-Tier Item Factor Structure
Further MIRT Applications
Descriptions of Images and Figures
References
Index
Отрывок из книги
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Series Editor
Chapter 5 covers several ways of describing the results of a MIRT analysis. One of the many challenges in understanding MIRT models is how to make sense of the parameter estimates and other statistical properties of multidimensional items/tests. This chapter presents both item- and test-level descriptives, including multidimensional item response surfaces, information functions, and other important components of standard MIRT output.
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