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Jingdan Zhu_Master Thesis.pdf (556.5 KB)

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Measurement Invariance Relationships between Multilevel Factor Models and Multigroup Factor Models

Zhu, Jingdan
http://rave.ohiolink.edu/etdc/view?acc_num=osu1605557022687951

Abstract Details

2020, Master of Science, Ohio State University, Psychology.
For multivariate data with different groups of individuals, two factor model approaches are available: multigroup factor models and multilevel factor models. The former was originally developed for a few groups while the latter requires a large number of groups. Except for a few articles in the literature (Jak, 2019; Jak & Jorgensen, 2017; Jak, Oort, & Dolan, 2013, 2014), not much attention is given to the relationship between the two approaches. For example, for both approaches, notions of measurement invariance are used: configural, metric, scalar, and strict invariance for multigroup models, and cross-level invariance for multilevel models. In this thesis we will investigate how cross-level invariance maps into multigroup scalar invariance and vice versa. The mapping is important for several reasons: (1) to understand the theoretical relationship between the two models, and (2) to detect and (3) to interpret multigroup scalar invariance violations. Checking cross-level invariance is informative for scalar invariance, and in the absence of scalar invariance, the level-2 factor structure of a multilevel factor model can help with the understanding of multigroup scalar invariance violation. The thesis has three chapters. In Chapter 1, the multilevel factor model is introduced with its notations and an illustrative example. In Chapter 2, the multigroup factor model is reviewed and the relationship between cross-level invariance and multigroup scalar invariance is mapped out. In Chapter 3, a set of demonstration simulation studies is presented to illustrate the conclusions from Chapter 2. Chapter 4 is a discussion chapter on the results from Chapter 3, which includes contributions and limitations, practical consequences, and future directions of research.
Paulus De Boeck (Advisor)
Jolynn Pek (Committee Member)
Duane Wegener (Committee Member)
68 p.
Quantitative Psychology
Measurement Invariance; Multilevel Factor Analysis; Multigroup Factor Analysis

Recommended Citations

Citations

  • Zhu, J. (2020). Measurement Invariance Relationships between Multilevel Factor Models and Multigroup Factor Models [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1605557022687951

    APA Style (7th edition)

  • Zhu, Jingdan. Measurement Invariance Relationships between Multilevel Factor Models and Multigroup Factor Models. 2020. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1605557022687951.

    MLA Style (8th edition)

  • Zhu, Jingdan. "Measurement Invariance Relationships between Multilevel Factor Models and Multigroup Factor Models." Master's thesis, Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1605557022687951

    Chicago Manual of Style (17th edition)

osu1605557022687951
175
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This open access ETD is published by The Ohio State University and OhioLINK.