Reliability of Summed Item Scores Using Structural Equation Modeling: An Alternative to Coefficient Alpha

By S. Green, Yanyun Yang. 2009

405 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/101fddaafcc4cee1fcd948cb240dd49201698f20

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In Computer Networks and Communications

In Management Science and Operations Research

In Social Psychology

Citations in the corpus

Commentary on Coefficient Alpha: A Cautionary Tale (2009, methodology): “We discuss an alternative model that allows for nonlinearity between factor scores and item scores for estimating reliability in a second article in the commentary on coefficient alpha ( Green & Yang, 2009 ).”
Testing Measurement Invariance and Comparing Latent Factor Means Within a Confirmatory Factor Analysis Framework (2011, methodology): “…Management, Δχ2 (5) = 119.38, p < .001, and Instructional Management, Δχ2 (5) = 58.91, p < .001, scales, thus the nonlinear SEM reliability estimates (Green & Yang 2009; Yang & Green, 2011) of .79 and .78 were computed for the Behavior Management and Instructional Management scales, respectively.”
Making Reliability Reliable (2016, background): “…studies such as Cortina (1993) and Schmitt (1996) offered influential lessons on alpha for organizational researchers, it is still commonly misconceived and widely misused (Cho & Kim, 2015; Dunn, Baguley, & Brunsden, 2013; Green & Yang, 2009a; Raykov, 2012; Sijtsma, 2009a; Yang & Green, 2011).”
Comparison of Reliability Measures Under Factor Analysis and Item Response Theory (2012, background): “Recently Psychometrika published a series of discussions on various reliability measures, their uses, common misconceptions about them, and theoretical issues remaining to be solved (Bentler, 2009; S. B. Green & Yang, 2009a, 2009b; Revelle & Zinbarg, 2009; Sijtsma, 2009a, 2009b).”
An evaluation of WLSMV and Bayesian methods for confirmatory factor analysis with categorical indicators (2014, methodology): “Several SEM methods have been proposed for ordered categorical data (e.g., Asparouhov and Muthén, 2010b; Flora and Curran, 2004; Green and Yang, 2009; Lee and Tang, 2006).”
Estimating Ordinal Reliability for Likert-Type and Ordinal Item Response Data: A Conceptual, Empirical, and Practical Guide. (2012, methodology): “Table 2 shows the Pearson correlations, Pearson covariances, and polychoric/tetrachoric correlations for the three items, the average correlations/covariance, and the respective alphas.”
Why Ordinal Variables Can (Almost) Always Be Treated as Continuous Variables: Clarifying Assumptions of Robust Continuous and Ordinal Factor Analysis Estimation Methods (2020, methodology): “In our view, the assessment of reliability based on an ordinal factor model (Green and Yang, 2009) is not necessarily superior to using a factor model that treats ordinal variables as continuous.”
Coefficient Alpha: A Reliability Coefficient for the 21st Century? (2011, methodology): “See Green and Hershberger (2000) and Green and Yang (2009a) for further discussion of this topic.”
Cronbach’s Coefficient Alpha (2015, methodology): “His intention of stimulating debate was successfully realized; in 2009, four comments on his paper (Bentler, 2009; Green & Yang, 2009a, 2009b; Revelle & Zinbarg, 2009), as well as his rejoinder (Sijtsma, 2009b), were published in Psychometrika.”
Best Alternatives to Cronbach's Alpha Reliability in Realistic Conditions: Congeneric and Asymmetrical Measurements (2016, background): “In this more realistic condition therefore (Green and Yang, 2009a; Yang and Green, 2011), α becomes a negatively biased reliability estimator (Graham, 2006; Sijtsma, 2009; Cho and Kim, 2015) and ω is always preferable to α (Dunn et al., 2014).”