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

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Beitragende

Abstract

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.

Details

OriginalspracheEnglisch
Aufsatznummer766 - 781
Seiten (von - bis)766-781
Seitenumfang16
FachzeitschriftEducational and psychological measurement : EPM ; a bimonthly journal devoted to the development and application of measures of individual differences
Jahrgang83
Ausgabenummer4
Frühes Online-DatumJuli 2022
PublikationsstatusVeröffentlicht - Aug. 2023
Peer-Review-StatusJa

Externe IDs

Scopus 85134612144
ORCID /0000-0003-1106-474X/work/151436754
PubMed 37398845
Mendeley 49578ffb-db16-3b55-9686-664eb876d2bc

Schlagworte

Schlagwörter

  • Coefficient alpha, Measurement, Multicomponent instrument, Parameter space, Population reliability to alpha discrepancy, Scale reliability, Single-factor model, Unidimensionality, coefficient alpha, measurement, multicomponent instrument, parameter space, population reliability to alpha discrepancy, scale reliability, single-factor model, unidimensionality