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Inference for Disattenuated Correlations

Jonas Moss

Applied Psychological Measurement2026https://doi.org/10.1177/01466216261440511article
AJG 2ABDC B
Weight
0.50

Abstract

When only summary statistics from published studies are available, the Hunter-Schmidt interval is the standard tool for inference on Spearman's disattenuated correlation, but it treats reliability estimates as known constants and ignores their sampling variability. We derive a simple delta method variance that accounts for the uncertainty of all estimates while requiring nothing beyond the summaries already at hand. Under bivariate normality of scores and coefficient alpha from a normal parallel model, the corrected interval is asymptotically valid. In simulations it achieves coverage near nominal, while Hunter-Schmidt can undercover substantially when reliability is imprecisely estimated.

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https://doi.org/https://doi.org/10.1177/01466216261440511

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@article{jonas2026,
  title        = {{Inference for Disattenuated Correlations}},
  author       = {Jonas Moss},
  journal      = {Applied Psychological Measurement},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1177/01466216261440511},
}

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Inference for Disattenuated Correlations

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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