Description
Measurement invariance exists when a scale functions equivalently across people and is therefore essential for making meaningful group comparisons. Often, measurement invariance is examined with independent and identically distributed data; however, there are times when the participants are clustered within units, creating dependency in the data. Researchers have taken different approaches to address this dependency when studying measurement invariance (e.g., Kim, Kwok, & Yoon, 2012; Ryu, 2014; Kim, Yoon, Wen, Luo, & Kwok, 2015), but there are no comparisons of the various approaches. The purpose of this master's thesis was to investigate measurement invariance in multilevel data when the grouping variable was a level-1 variable using five different approaches. Publicly available data from the Early Childhood Longitudinal Study-Kindergarten Cohort (ECLS-K) was used as an illustrative example. The construct of early behavior, which was made up of four teacher-rated behavior scales, was evaluated for measurement invariance in relation to gender. In the specific case of this illustrative example, the statistical conclusions of the five approaches were in agreement (i.e., the loading of the externalizing item and the intercept of the approaches to learning item were not invariant). Simulation work should be done to investigate in which situations the conclusions of these approaches diverge.
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Title
- Approaches to studying measurement invariance in multilevel data with a level-1 grouping variable
Contributors
- Gunn, Heather (Author)
- Grimm, Kevin J. (Thesis advisor)
- Aiken, Leona S. (Committee member)
- Suk, Hye Won (Committee member)
- Arizona State University (Publisher)
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2016
Subjects
Resource Type
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Note
- thesisPartial requirement for: M.A., Arizona State University, 2016
- bibliographyIncludes bibliographical references (pages 48-51)
- Field of study: Psychology
Citation and reuse
Statement of Responsibility
by Heather Gunn