Full metadata
Title
Assessing measurement invariance and latent mean differences with bifactor multidimensional data in structural equation modeling
Description
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. Datasets were generated using a bifactor model with different factor structures and were analyzed with bifactor and single-factor models to assess misspecification effects on assessments of MI and latent mean differences. As baseline models, the bifactor models fit data well and had minimal bias in latent mean estimation. However, the low convergence rates of fitting bifactor models to data with complex structures and small sample sizes caused concern. On the other hand, effects of fitting the misspecified single-factor models on the assessments of MI and latent means differed by the bifactor structures underlying data. For data following one general factor and one group factor affecting a small set of indicators, the effects of ignoring the group factor in analysis models on the tests of MI and latent mean differences were mild. In contrast, for data following one general factor and several group factors, oversimplifications of analysis models can lead to inaccurate conclusions regarding MI assessment and latent mean estimation.
Date Created
2018
Contributors
- Xu, Yuning (Author)
- Green, Samuel (Thesis advisor)
- Levy, Roy (Committee member)
- Thompson, Marilyn (Committee member)
- Arizona State University (Publisher)
Topical Subject
Resource Type
Extent
vi, 55-60 pages : illustrations
Language
eng
Copyright Statement
In Copyright
Primary Member of
Peer-reviewed
No
Open Access
No
Handle
https://hdl.handle.net/2286/R.I.50462
Statement of Responsibility
by Yuning Xu
Description Source
Viewed on January 23, 2019
Level of coding
full
Note
thesis
Partial requirement for: Ph.D., Arizona State University, 2018
bibliography
Includes bibliographical references (pages 55-60)
Field of study: Educational psychology
System Created
- 2018-10-01 08:01:03
System Modified
- 2021-08-26 09:47:01
- 3 years 3 months ago
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