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The Role of Item Distributions on Reliability Estimation: The Case of Cronbach’s Coefficient Alpha

Oscar L. Olvera Astivia, Edward Kroc, Bruno D. Zumbo

2020Educational and Psychological Measurement19 citationsDOIOpen Access PDF

Abstract

Simulations concerning the distributional assumptions of coefficient alpha are contradictory. To provide a more principled theoretical framework, this article relies on the Fréchet–Hoeffding bounds, in order to showcase that the distribution of the items play a role on the estimation of correlations and covariances. More specifically, these bounds restrict the theoretical correlation range [−1, 1] such that certain correlation structures may be unfeasible. The direct implication of this result is that coefficient alpha is bounded above depending on the shape of the distributions. A general form of the Fréchet–Hoeffding bounds is derived for discrete random variables. R code and a user-friendly shiny web application are also provided so that researchers can calculate the bounds on their data.

Topics & Concepts

Cronbach's alphaAlpha (finance)Reliability (semiconductor)Random variableBounded functionRange (aeronautics)Code (set theory)MathematicsCorrelation coefficientApplied mathematicsComputer scienceStatisticsDiscrete mathematicsMathematical analysisPhysicsPsychometricsPower (physics)Set (abstract data type)Quantum mechanicsProgramming languageMaterials scienceComposite materialStatistical Distribution Estimation and ApplicationsMulti-Criteria Decision MakingAdvanced Statistical Methods and Models
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