KR20 and KR21 for Some Nondichotomous Data (It’s Not Just Cronbach’s Alpha)

• Published in: Educational and psychological measurement Vol. 81; no. 6; pp. 1172 - 1202
• Main Author: Foster, Robert C.
• Format: Journal Article
• Language: English
• Published: Los Angeles, CA SAGE Publications 01-12-2021; SAGE PUBLICATIONS, INC
• Subjects: Computation; Cronbach's alpha; Data; Mathematical Formulas; Quantitative psychology; Reliability; Simulation; Test Reliability; KR-20; KR-21; Cronbach’s alpha; exponential families; reliability
• ISSN: 0013-1644; 1552-3888
• DOI: 10.1177/0013164421992535

This article presents some equivalent forms of the common Kuder–Richardson Formula 21 and 20 estimators for nondichotomous data belonging to certain other exponential families, such as Poisson count data, exponential data, or geometric counts of trials until failure. Using the generalized framework of Foster (2020), an equation for the reliability for a subset of the natural exponential family have quadratic variance function is derived for known population parameters, and both formulas are shown to be different plug-in estimators of this quantity. The equivalent Kuder–Richardson Formulas 20 and 21 are given for six different natural exponential families, and these match earlier derivations in the case of binomial and Poisson data. Simulations show performance exceeding that of Cronbach’s alpha in terms of root mean square error when the formula matching the correct exponential family is used, and a discussion of Jensen’s inequality suggests explanations for peculiarities of the bias and standard error of the simulations across the different exponential families.