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Investigation of measurement invariance (MI) commonly assumes correct specification of dimensionality across multiple groups. Although research shows that violation of the dimensionality assumption can cause bias in model parameter estimation

Investigation of measurement invariance (MI) commonly assumes correct specification of dimensionality across multiple groups. Although research shows that violation of the dimensionality assumption can cause bias in model parameter estimation for single-group analyses, little research on this issue has been conducted for multiple-group analyses. This study explored the effects of mismatch in dimensionality between data and analysis models with multiple-group analyses at the population and sample levels.

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Date Created
  • 2018
Resource Type
  • Text
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    Note
    • Partial requirement for: Ph.D., Arizona State University, 2018
      Note type
      thesis
    • Includes bibliographical references (pages 55-60)
      Note type
      bibliography
    • Field of study: Educational psychology

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    by Yuning Xu

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