The Impact of Within-Template Systematic Variation on Response Models

Master's Thesis
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Abstract

With item response data, systematic variation within nested groups of generated items may negatively impact the estimation of item and person parameters. This paper studies a model that can capture the multilevel structure of the data and explain within-template systematic variability. The goal of this model is twofold. First, explaining and removing non-random error may improve ability and item parameter estimates. And second, finding systematic variation can bring insights into the educational process. Simulation results are discussed at length.

Attributes

Attribute NameValues
URN
  • etd-12052013-125736

Author Quinn Nathaniel Lathrop
Advisor Ying Cheng
Contributor Scott Maxwell, Committee Member
Contributor Lijuan Wang, Committee Member
Contributor Ying Cheng, Committee Chair
Degree Level Master's Thesis
Degree Discipline Psychology
Degree Name MA
Defense Date
  • 2013-12-02

Submission Date 2013-12-05
Country
  • United States of America

Subject
  • computerized assessment

  • generated items

  • explanatory IRT

  • multilevel models

  • item response theory

Publisher
  • University of Notre Dame

Language
  • English

Record Visibility Public
Content License
  • All rights reserved

Departments and Units

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