BEST PRACTICES IN STRUCTURAL EQUATION MODELING

By R. Mueller, G. R. Hancock. 2007

424 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/d1cd5e23152c35a566aaafcd6aeadb8870405545

How researchers see this paper

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

In Computer Networks and Communications

1. Young Kim
2. Todd Lubart
3. M. Besançon
4. Baptiste Barbot

In Management Science and Operations Research

1. Young Kim
2. Todd Lubart
3. M. Besançon
4. Baptiste Barbot

In Statistics and Probability

1. Young Kim
2. Paul Gilbert
3. Todd Lubart
4. M. Besançon
5. Baptiste Barbot

Citations in the corpus

• Initial Development and Validation of the School Belongingness Scale (2016, neutral): “Latent construct reliability was also calculated for latent structures and coefficients (H) ≥ .70 were considered adequate (Mueller and Hancock 2008).”
• The generality-specificity of creativity: Exploring the structure of creative potential with EPoC (2016, methodology): “…often occurring with MTMM data under the CFA framework (Kenny & Kashy, 1992), the variance of the higher order thinking-process factor was set to 1 (e.g., Mueller & Hancock, 2008) and the loadings between the general thinking-process factor and both first-order factors were set to be equal.”
• Organizational resilience and employee work-role performance after a crisis situation: exploring the effects of organizational resilience on internal crisis communication (2020, methodology): “The two-step (phase) process is recommended over an all-in-one approach, since it allows a researcher to realize misspecification and address it before the structure is assessed among latent constructs (Hair, Black, Babin, & Anderson, 2010; Mueller & Hancock, 2008).”
• The development of compassionate engagement and action scales for self and others (2017, background): “The use of cross-sectional data does not invalidate this specific approach (e.g., [56, 89]).”
• Modeling factors explaining the acceptance, actual use and satisfaction of nurses using an Electronic Patient Record in acute care settings: An extension of the UTAUT (2015, neutral): “Several types of fit measures (absolute, parsimonious and incremental indices) were considered to assess data-model fit [60,65].”