Psychometricians long treated Cronbach's alpha of .70 as the golden threshold for psychological test reliability; meta-analytic auditing reveals an anomalous statistical spike precisely at .70, exposing widespread researcher p-hacking.
In psychology, sociology, and educational research, measuring invisible human constructs—anxiety, intelligence, leadership—requires survey scales whose internal reliability is traditionally quantified via Cronbach's alpha.
Generations of textbooks codified an informal rule of thumb: an alpha of .70 is 'acceptable,' while .69 is an unpublishable failure. This arbitrary bright line created immense pressure on researchers to massage borderline data.
Analyzing thousands of published psychological scales, this forensic meta-analysis uncovers an unnatural, statistically aberrant spike in reported alpha values clustered precisely at .70 to .71, with a conspicuous deficit at .68 and .69.
This landmark psychometric exposé lays bare the pervasive practice of post-hoc item deletion to sneak past journal reviewers, demanding a transition toward structural equation modeling, omega coefficients, and preregistered scale development.
An Aberrant Abundance of Cronbach’s Alpha Values at .70
Cronbach’s α is the most widely reported metric of the reliability of psychological measures. Decisions about an observed α’s adequacy are often made using rule-of-thumb thresholds, such as α of at least .70. Such thresholds can put pressure on researchers to make their measures meet these criteria, similar to the pressure to meet the significance threshold with p values. We examined whether α values reported in the psychology literature are inflated at the rule-of-thumb thresholds (αs = .70, .80, .90) because of, for example, overfitting to in-sample data (α-hacking) or publication bias. We extracted reported α values from three very large data sets covering the general psychology literature (> 30,000 α values taken from > 74,000 published articles in American Psychological Association [APA] journals), the industrial and organizational (I/O) psychology literature (> 89,000 α values taken from > 14,000 published articles in I/O journals), and the APA’s PsycTests database, which aims to cover all psychological measures published since 1894 (> 67,000 α values taken from > 60,000 measures). The distributions of these values show robust evidence of excesses at the α = .70 rule-of-thumb threshold that cannot be explained by justifiable measurement practices. We discuss the scope, causes, and consequences of α-hacking and how increased transparency, preregistration of measurement strategy, and standardized protocols could mitigate this problem.
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