On the Importance of Coefficient Alpha for Measurement Research: Loading Equality Is Not Necessary for Alpha's Utility as a Scale Reliability Index.

coefficient alpha measurement multicomponent instrument parameter space population reliability to alpha discrepancy scale reliability single-factor model unidimensionality

Journal

Educational and psychological measurement
ISSN: 1552-3888
Titre abrégé: Educ Psychol Meas
Pays: United States
ID NLM: 0372767

Informations de publication

Date de publication:
Aug 2023
Historique:
pmc-release: 01 08 2024
medline: 3 7 2023
pubmed: 3 7 2023
entrez: 3 7 2023
Statut: ppublish

Résumé

The population relationship between coefficient alpha and scale reliability is studied in the widely used setting of unidimensional multicomponent measuring instruments. It is demonstrated that for any set of component loadings on the common factor, regardless of the extent of their inequality, the discrepancy between alpha and reliability can be arbitrarily small in any considered population and hence practically ignorable. In addition, the set of parameter values where this discrepancy is negligible is shown to possess the same dimensionality as that of the underlying model parameter space. The article contributes to the measurement and related literature by pointing out that (a) approximate or strict loading identity is not a necessary condition for the utility of alpha as a trustworthy index of scale reliability, and (b) coefficient alpha can be a dependable reliability measure with any extent of inequality in the component loadings.

Identifiants

pubmed: 37398845
doi: 10.1177/00131644221104972
pii: 10.1177_00131644221104972
pmc: PMC10311953
doi:

Types de publication

Journal Article

Langues

eng

Pagination

766-781

Informations de copyright

© The Author(s) 2022.

Déclaration de conflit d'intérêts

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Références

Educ Psychol Meas. 2019 Feb;79(1):200-210
pubmed: 30636788
Multivariate Behav Res. 1997 Oct 1;32(4):329-53
pubmed: 26777071
Psychol Methods. 2018 Sep;23(3):412-433
pubmed: 28557467
Psychometrika. 2009 Mar;74(1):107-120
pubmed: 20037639
Psychometrika. 1967 Mar;32(1):1-13
pubmed: 5232569

Auteurs

Tenko Raykov (T)

Michigan State University, East Lansing, USA.

James C Anthony (JC)

Michigan State University, East Lansing, USA.

Natalja Menold (N)

Technical University Dresden, Germany.

Classifications MeSH