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Statistical Models for Test Equating, Scaling, and Linking

Overview of attention for book
Cover of 'Statistical Models for Test Equating, Scaling, and Linking'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 A Statistical Perspective on Equating Test Scores
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    Chapter 2 Equating Test Scores: Toward Best Practices
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    Chapter 3 Scoring and Scaling Educational Tests
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    Chapter 4 Statistical Models for Vertical Linking
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    Chapter 5 An Empirical Example of Change Analysis by Linking Longitudinal Item Response Data From Multiple Tests
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    Chapter 6 How to Average Equating Functions, If You Must
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    Chapter 7 New Approaches to Equating With Small Samples
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    Chapter 8 Using Exponential Families for Equating
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    Chapter 9 An Alternative Continuization Method: The Continuized Log-Linear Method
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    Chapter 10 Equating Through Alternative Kernels
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    Chapter 11 A Bayesian Nonparametric Model for Test Equating
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    Chapter 12 Generalized Equating Functions for NEAT Designs
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    Chapter 13 Local Observed-Score Equating
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    Chapter 14 A General Model for IRT Scale Linking and Scale Transformations
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    Chapter 15 Linking With Nonparametric IRT Models
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    Chapter 16 Applications of Asymptotic Expansion in Item Response Theory Linking
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    Chapter 17 Evaluating the Missing Data Assumptions of the Chain and Poststratification Equating Methods
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    Chapter 18 Robustness of IRT Observed-Score Equating
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    Chapter 19 Hypothesis Testing of Equating Differences in the Kernel Equating Framework
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    Chapter 20 Applying Time-Series Analysis to Detect Scale Drift
Attention for Chapter 18: Robustness of IRT Observed-Score Equating
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Citations

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Chapter title
Robustness of IRT Observed-Score Equating
Chapter number 18
Book title
Statistical Models for Test Equating, Scaling, and Linking
Published by
Springer New York, September 2010
DOI 10.1007/978-0-387-98138-3_18
Book ISBNs
978-0-387-98137-6, 978-0-387-98138-3
Authors

C. A. W. Glas, Anton A. Béguin

Editors

Alina A. von Davier

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 40%
Professor 1 20%
Lecturer 1 20%
Student > Doctoral Student 1 20%
Readers by discipline Count As %
Social Sciences 3 60%
Psychology 1 20%
Computer Science 1 20%

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