Registry · Priors

construct.performance_feedback correlates construct.organizational_commitment

normal · informative · 2 studies · N = 35,754

Distribution

Storage scale (Fisher z)
Prior PDF · normalnormal distribution. Storage scale (Fisher z). 95% CI ≈ [0.243, 0.571]; mean ≈ 0.407.0.07170.2390.4070.5750.742z0density

mean ≈ 0.407 · 95% CI ≈ [0.243, 0.571]

Reader scale (r)
Prior PDF · normalnormal distribution. Reader scale (r). 95% CI ≈ [0.246, 0.526]; mean ≈ 0.386.0.1010.2430.3860.5290.671r0density

mean ≈ 0.386 · 95% CI ≈ [0.246, 0.526]

Intervals

Confidence interval (95%) — uncertainty about the mean ρ
[0.24, 0.52]
Credibility interval (95%) — distribution of the true effect across settings (the Bayesian prior)
[0.19, 0.55]
I² (heterogeneity) — share of total variance from between-study differences
99%

The true effect varies across settings — moderators likely matter.

SD_ρ>0 — true effect varies across settings; likely moderated (observed-score scale until artifact correction, PRN-058)

Evidence provenance

published ρ=0.39 (k=2, high heterogeneity (I²=0.99)); no primary-deployment evidence yet

Sourceρ (r)Scope
Published literature0.39k = 2 · N = 35,754

No primary-deployment evidence yet — this prior rests on published literature alone. As anonymized, aggregated effect sizes from real deployments are contributed, they appear here as a distinct, publication-bias-free source, fused with the literature into a posterior estimate.

Code

Drop this prior straight into your model. Snippets generated from the synthesized distribution + parameters.

target += normal_lpdf(beta | 0.407011, 0.0838343);
beta = pm.Normal("beta", mu=0.407011, sigma=0.0838343)
brms::prior(normal(0.407011, 0.0838343), class = "b")
# base R sample
rnorm(N, mean = 0.407011, sd = 0.0838343)
np.random.normal(loc=0.407011, scale=0.0838343, size=N)

Parameters

FamilyParameters
normalI2 = 0.9897, mu = 0.4070, sigma = 0.08383, r_mean = 0.3859, k_studies = 2.000, tau_squared = 0.01181

Synthesis

Method
random_effects_meta
Informativeness
informative
Replication status
meta-analytic
k_studies
2
n_total
35,754
Last updated
2026-05-30T22:53:15.685Z

Quality distribution

GradeCount
A1
B1
C0
D0

Contributing effect sizes

Effect-size detail pages land with a later sub-ticket; for now, ids link to the filtered list. Browse all rows via /registry/effects.