Assumptions of cross-level measurement and structural invariance in the analysis of multilevel data: Problems and solutions

By Michael Zyphur, Seth A. Kaplan, Michal Christian. 2008

73 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Organizational Behavior and Human Resource Management, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/75789617e6b987231e8fe1ad1d8a04c9d76a6931

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Management Science and Operations Research

1. Jeroen K. Vermunt
2. C. Sacramento
3. Sang Eun Woo
4. S. Aryee
5. Louis Tay
6. Ieva Martinaityte

In Organizational Behavior and Human Resource Management

1. Jeroen K. Vermunt
2. C. Sacramento
3. Sang Eun Woo
4. S. Aryee
5. Louis Tay
6. Ieva Martinaityte
7. Osman M. Karatepe

In Sociology and Political Science

1. Jeroen K. Vermunt
2. C. Sacramento
3. Sang Eun Woo
4. S. Aryee
5. Louis Tay
6. Ieva Martinaityte

Citations in the corpus

• A Conceptual and Methodological Framework for Psychometric Isomorphism (2014, methodology): “This is important when contextual analysis is conducted and coefficients across levels are compared (Enders & Tofighi, 2007; Hofmann & Gavin, 1998; Zyphur et al., 2008).”
• Delighting the Customer: Creativity-Oriented High-Performance Work Systems, Frontline Employee Creative Performance, and Customer Satisfaction (2019, methodology): “Given the multilevel structure of the data, we present the disaggregated correlations in Table 1, which includes both the within- and between-level correlations between all variables included in the testing of the model (e.g., Zyphur et al., 2008).”