Performance of Coefficient Alpha and Its Alternatives: Effects of Different Types of Non-Normality.

ABSTRACT: We examined the performance of coefficient alpha and its potential competitors (ordinal alpha, omega total, Revelle's omega total [omega RT], omega hierarchical [omega h], greatest lower bound [GLB], and coefficient H) with continuous and discrete data having different types of non-normality. Results showed the estimation bias was acceptable for continuous data with varying degrees of non-normality when the scales were strong (high loadings). This bias, however, became quite large with moderate strength scales and increased with increasing non-normality. For Likert-type scales, other than omega h, most indices were acceptable with non-normal data having at least four points, and more points were better. For different exponential distributed data, omega RT and GLB were robust, wherea

SUBMITTER: Xiao L 

PROVIDER: S-EPMC9806521 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature