Name: Introduction to Item Response Theory Models and Applications By James Carlson
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Introduction to Item Response Theory Models and Applications Summary

Introduction to Item Response Theory Models and Applications by James Carlson

This is a highly accessible, comprehensive introduction to item response theory (IRT) models and their use in various aspects of assessment/testing. The book employs a mixture of graphics and simulated data sets to ease the reader into the material and covers the basics required to obtain a solid grounding in IRT.

Written in an easily accessible way that assumes little mathematical knowledge, Carlson presents detailed descriptions of several commonly used IRT models, including those for items scored on a two-point (dichotomous) scale such as correct/incorrect, and those scored on multiple-point (polytomous) scales, such as degrees of correctness. One chapter describes a model in-depth and is followed by a chapter of instructions and illustrations showing how to apply the models to the reader's own work.

This book is an essential text for instructors and higher level undergraduate and postgraduate students of statistics, psychometrics, and measurement theory across the behavioral and social sciences, as well as testing professionals.

Introduction to Item Response Theory Models and Applications Reviews

Carlson's book is a very clear and well-written introduction to item response theory models that should prove very useful to a wide range of students, instructors, researchers and professionals who want to understand the basics of this useful methodology. -- Lisa L. Harlow, professor of psychology at the University of Rhode Island, USA, and series editor for the Multivariate Applications Series (sponsored by SMEP).

About James Carlson

James E. Carlson received his Ph.D. from the University of Alberta, Canada, specializing in applied statistics. He was professor of education at the universities of Pittsburgh, USA, and Ottawa, Canada. He also held psychometric positions at testing organizations and the National Assessment Governing Board, U. S. Department of Education. He is a former editor of the Journal of Educational Measurement and has authored two book chapters and a number of journal articles and research reports.

Introduction
2. Background and Terminology
4. Contents of the Following Chapters
Models for Dichotomously-Scored Items
2. Introduction
4. Classical Test theory Models
5. The Model
  
  Item Parameters and their Estimates
  
  Test Parameters and their Estimates
6. Item Response Theory Models
7. Introduction
  
  The Normal Ogive Three-Parameter Item Response Theory Model
  
  The Three-Parameter Logistic (3PL) Model
  
  Special Cases: The Two-Parameter and One-Parameter Logistic Models
  
  Relationships Between Probabilities of Alternative Responses
  
  Transformations of Scale
  
  Effects of Changes in Parameters
  
  The Test Characteristic Function
  
  The Item Information Function
  
  The Test Information Function and Standard Errors of Measurement
8. IRT Estimation Methodology
9. Estimation of Item Parameters
  
  Estimation of Proficiency
  
  Indeterminacy of the Scale in IRT Estimation
10. Summary
Analyses of Dichotomously-Scored Item and Test Data
2. Introduction
4. Example Classical Test Theory Analyses with a Small Dataset
6. Test and Item Analyses with a Larger Dataset
7. CTT Item and Test Analysis Results
8. IRT Item and Test Analysis
9. IRT Software
  
  Missing Data
  
  Iterative Estimation Methodology
  
  Model Fit
10. IRT Analyses Using PARSCALE
11. PARSCALE Terminology
  
  Some PARSCALE Options
  
  PARSCALE Item Analysis
  
  PARSCALE Test Analyses
12. IRT Analyses Using flexMIRT
13. flexMIRT Terminology
  
  Some flexMIRT Options
  
  flexMIRT Item Analyses and Comparisons Between Programs
  
  flexMIRT Test Analyses and Comparisons Between Programs
14. Using IRT Results to Evaluate Items and Tests
15. Evaluating Estimates of Item Parameters
  
  Evaluating Fit of Models to Items
  
  Evaluating Tests as a Whole or Subsets of Test Items
16. Equating, Linking, and Scaling
17. Equating
  
  Linking
  
  Scaling
  
  Vertical Scaling
18. Summary
Models for Polytomously-Scored Items
2. Introduction
4. The Nature of Polytomously-Scored Items
6. Conditional Probability Forms of Models for Polytomous Items
8. Probability-of-Response Form of the Polytomous Models
9. The 2PPC Model
  
  The GPC Model
  
  The Graded Response (GR) Model
10. Additional Characteristics of the GPC Model
11. Effects of Changes in Parameters
  
  Alternative Parameterizations
  
  The Expected Score Function
  
  Functions of Scoring at or Above Categories
  
  Comparison of Conditional Response and P+ Functions
  
  Item Mapping and Standard Setting
  
  The Test Characteristic Function
  
  The Item Information Function
  
  The Item Category Information Function
  
  The Test Information Function
  
  Conditional Standard Errors of Measurement
12. Summary
Analyses of Polytomously-Scored Item and Test Data
2. Generation of Example Data
4. Classical Test Theory Analyses
5. Item Analyses
  
  Test Analyses
6. IRT Analyses
7. PARSCALE Item Analyses
  
  flexMIRT Item Analyses and Comparisons with PARSCALE
8. Additional Methods of Using IRT Results to Evaluate Items
9. Evaluating Estimates of Item Parameters
  
  Evaluating Fit of Models to Item Data
  
  Additional Graphical Methods
10. Test Analyses
11. PARSCALE Test Analyses
  
  flexMIRT Test Analyses
12. Placing the Results from Different Analyses on the Same Scale
14. Summary
Multidimensional Item Response Theory Models
2. Introduction
4. The Multidimensional 3PL Model for Dichotomous Items
6. The Multidimensional 2PL Model for Dichotomous Items
8. Is there a Multidimensional 1PL Model for Dichotomous Items
10. Further Comments on MIRT Models
11. Alternate Parameterizations
  
  Additional Analyses of MIRT Data
12. Noncompensatory MIRT Models
14. MIRT Models for Polytomous Data
16. Summary
Analyses of Multidimensional Item Response Data
2. Response Data Generation
4. MIRT Computer Software
6. MIRT and Factor analyses
8. flexMIRT analyses of Example Generated Data
9. One-dimensional Solution with Two-Dimensional Data
  
  Two-dimensional Solution
10. Summary
Overview of More Complex Item Response Theory Models
2. Some More Complex Unidimensional Models
3. Multigroup Models
  
  Adaptive Testing
  
  Mixture Models
  
  Hierarchical Rater Models
  
  Testlet Models
4. More General MIRT Models: Some Further Reading
5. Hierarchical Models
6. Cognitive Diagnostic Models
8. Summary

References

Appendix A. Some Technical Background

1. Slope of the 3PL Curve at the Inflection Point where

2. Simplifying Notation for GPC Expressions

3. Some Characteristics of GPC Model Items

Peaks of Response Curves

Crossing Point of Pk and Pk-1

Crossing Point of P0 and P2 for m = 3

Symmetry in the Case of m = 3

Limits of the Expected Score Function

Appendix B. Item Category Information Functions

Appendix C. Item Generating Parameters and Classical and IRT Parameter Estimates

Index

Additional information

Sku

NPB9780367476922

ISBN 13

9780367476922

ISBN 10

0367476924

Title

Introduction to Item Response Theory Models and Applications by James Carlson

Author

James Carlson

Series

Multivariate Applications Series

Condition

New

Binding type

Hardback

Publisher

Taylor & Francis Ltd

Year published

2020-10-13

Number of pages

166

Prizes

N/A

Cover note

Book picture is for illustrative purposes only, actual binding, cover or edition may vary.

Note

This is a new book - be the first to read this copy. With untouched pages and a perfect binding, your brand new copy is ready to be opened for the first time

Introduction to Item Response Theory Models and Applications James Carlson

Introduction to Item Response Theory Models and Applications by James Carlson

Summary

Introduction to Item Response Theory Models and Applications Summary

Introduction to Item Response Theory Models and Applications by James Carlson

Introduction to Item Response Theory Models and Applications Reviews

About James Carlson

Table of Contents

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