A Note on Structural Equation Modeling Estimates of Reliability

By Yanyun Yang, S. Green. 2010

114 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/c8b7fa2da9e424b3d17d0248e93501f290f87a31

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In Computer Networks and Communications

In Management Science and Operations Research

Citations in the corpus

Coefficient Alpha: A Reliability Coefficient for the 21st Century? (2011, background): “As demonstrated by Yang and Green (2010a), the linear SEM estimates yield biased estimate if the structural model is misspecified.”
Edinburgh Handedness Inventory – Short Form: A revised version based on confirmatory factor analysis (2014, unknown): “An advantage of Raykov’s r is that unlike Cronbach’s a it does not assume all scale items equally contribute to a factor’s variance and can allow for correlated error variances (Yang & Green, 2010).”
“My Questionnaire is Too Long!” The assessments of motivational-affective constructs with three-item and single-item measures (2014, methodology): “…omega is based on parameter estimates (i.e., estimates of factor loadings and factor variances) that are derived for a certain CFA model, the proper interpretation of omega requires that the target model provides a good fit to the empirical data (Bentler, 2009; McDonald, 1999; Yang & Green, 2010).”
A journey around alpha and omega to estimate internal consistency reliability (2017, methodology): “On the other hand, the more cor- rect estimates based on SEM methods require large samples in order to achieve stable results (Yang & Green, 2010) therefore the costs for the pilot study could rise disproportionately due to the adoption of this methodology.”
Self-determination and STEM education: Effects of autonomy, motivation, and self-regulated learning on high school math achievement (2015, methodology): “To examine reliability in study measures, we used McDonald's Omega (McDonald, 1999) instead of Cronbach's alpha, because the latter requires that the factor loadings are the same for all items (Yang & Green, 2010) and that the nature of the data is continuous (Elosua & Zumbo, 2008).”
Use Omega Rather than Cronbach’s Alpha for Estimating Reliability. But… (2020, background): “Green and Yang (2009), Yang & Green (2010)) discuss SEM approaches to the estimation of reliability (also see Graham, 2006; Raykov, 1997b) and favor SEM because it offers the analyst considerable flexibility in how the measurement model is specified.”
Your Coefficient Alpha Is Probably Wrong, but Which Coefficient Omega Is Right? A Tutorial on Using R to Obtain Better Reliability Estimates (2020, background): “Furthermore, Yang and Green (2010) showed that ωu estimates are largely robust when the estimated model contains more factors than the true model, even with samples as small as 50.”