Registry · Priors

construct.performance_feedback correlates construct.job_satisfaction

normal · informative · 2 studies · N = 91,361

Distribution

Storage scale (Fisher z)
Prior PDF · normalnormal distribution. Storage scale (Fisher z). 95% CI ≈ [0.393, 0.611]; mean ≈ 0.502.0.2790.3910.5020.6140.725z0density

mean ≈ 0.502 · 95% CI ≈ [0.393, 0.611]

Reader scale (r)
Prior PDF · normalnormal distribution. Reader scale (r). 95% CI ≈ [0.378, 0.550]; mean ≈ 0.464.0.2890.3760.4640.5510.639r0density

mean ≈ 0.464 · 95% CI ≈ [0.378, 0.550]

Intervals

Confidence interval (95%) — uncertainty about the mean ρ
[0.37, 0.55]
Credibility interval (95%) — distribution of the true effect across settings (the Bayesian prior)
[0.35, 0.57]
I² (heterogeneity) — share of total variance from between-study differences
100%

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=0.46 (k=2, high heterogeneity (I²=1.00)); no primary-deployment evidence yet

Sourceρ (r)Scope
Published literature0.46k = 2 · N = 91,361

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 | 0.502166, 0.0557618);
beta = pm.Normal("beta", mu=0.502166, sigma=0.0557618)
brms::prior(normal(0.502166, 0.0557618), class = "b")
# base R sample
rnorm(N, mean = 0.502166, sd = 0.0557618)
np.random.normal(loc=0.502166, scale=0.0557618, size=N)

Parameters

FamilyParameters
normalI2 = 0.9954, mu = 0.5022, sigma = 0.05576, r_mean = 0.4638, k_studies = 2.000, tau_squared = 0.005263

Synthesis

Method
random_effects_meta
Informativeness
informative
Replication status
meta-analytic
k_studies
2
n_total
91,361
Last updated
2026-05-30T22:53:15.201Z

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.