Please use this identifier to cite or link to this item: https://doi.org/10.1037/1089-2699.12.2.127
Title: Assumptions of Cross-Level Measurement and Structural Invariance in the Analysis of Multilevel Data: Problems and Solutions
Authors: Zyphur, M.J. 
Kaplan, S.A.
Christian, M.S.
Keywords: constraint
cross-level
invariance
measurement
multilevel
Issue Date: 2008
Citation: Zyphur, M.J., Kaplan, S.A., Christian, M.S. (2008). Assumptions of Cross-Level Measurement and Structural Invariance in the Analysis of Multilevel Data: Problems and Solutions. Group Dynamics 12 (2) : 127-140. ScholarBank@NUS Repository. https://doi.org/10.1037/1089-2699.12.2.127
Abstract: This article demonstrates assumptions of invariance that researchers often implicitly make when analyzing multilevel data. The first set of assumptions is measurement-based and corresponds to the fact that researchers often conduct single-level exploratory and confirmatory factor analyses, and reliability analyses, with multilevel data. The second assumption, that of structural invariance, is engineered into the common multilevel random coefficient model, in that such analyses impose structural invariance across multiple levels of analysis when lower-level relationships represent both between- and within-groups effects. The nature of these assumptions, and ways to address their tenability, are explored from a conceptual standpoint. Then an empirical example of these assumptions and ways to address them is provided. © 2008 American Psychological Association.
Source Title: Group Dynamics
URI: http://scholarbank.nus.edu.sg/handle/10635/44660
ISSN: 10892699
DOI: 10.1037/1089-2699.12.2.127
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