A low alpha for an error-prone covariate can attenuate, inflate, or artificially produce a spurious effect (phantom effect) in the coefficient of a perfectly reliable predictor¶

Claim · All claims
Evidence · 1 study · theoretical r3 · q1
Currency · newest study 2025 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q1 i? In multiple regression with an error-prone covariate, the predictor's coefficient becomes a weighted sum that can be biased in either direction, including producing a phantom effect. → Steffen Zitzmann 2025

Evidence¶

Steffen Zitzmann 2025¶

Steffen Zitzmann, Gabe A. Orona. (2025). Why We Might Still be Concerned About Low Cronbach's Alphas in Domain-specific Knowledge Tests. Educational Psychology Review. https://doi.org/10.1007/s10648-025-10015-5

q1 · i? · theoretical · r3

Analytical derivation for a multiple regression where only the covariate is error-prone: the authors show the predictor's coefficient is biased, and that "a low alpha can lead to its attenuation" or inflation or a spurious effect. A worked quasiexperimental example yields β* = 0.15 where the true effect is 0.00.

"this means for an existing effect of the predictor that a low alpha can lead to its attenuation. Also, it can inflate the effect or even artificially produce a spurious effect (also referred to as phantom effect; e.g., Pokropek, 2015; Televantou et al., 2015), calling into question"

Discussion¶

Related Claims¶

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