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Meta‐Analysis of Coefficient Alpha: A Reliability Generalization Study
Author(s) -
Greco Lindsey M.,
O'Boyle Ernest H.,
Cockburn Bethany S.,
Yuan Zhenyu
Publication year - 2018
Publication title -
journal of management studies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.398
H-Index - 184
eISSN - 1467-6486
pISSN - 0022-2380
DOI - 10.1111/joms.12328
Subject(s) - generalization , reliability (semiconductor) , alpha (finance) , statistics , benchmark (surveying) , meta analysis , econometrics , scale (ratio) , mathematics , psychology , computer science , cronbach's alpha , psychometrics , geography , physics , power (physics) , medicine , cartography , mathematical analysis , quantum mechanics
Increasing precision of measurement is a goal of scientific advancement, but Nunnally's (1978) .70 benchmark for coefficient alpha (alpha) has remained the omnibus test for reliability for nearly 40 years. This likely arises due to there only being scattered empirical evidence of the degree to which the field has met or surpassed this standard. Using meta‐analytic techniques known as reliability generalization (RG), we cumulate alphas across 36 commonly used individual differences, attitudes, and behaviours from 1675 independent samples ( N = 991,588). Our primary finding is that alphas almost always exceed .70 and generally fall above .80. In addition, we identified factors that moderate alpha including the specific measure used, the number of scale items, and the rater. The study provides baseline alphas that can be used for research planning and design; it also offers best practices for RG and notes the benefits of RG for understanding systematic fluctuations in reliability.