Registry · Priors

construct.authentic_leadership predicts construct.job_satisfaction

normal · informative · 2 studies · N = 12,751

Distribution

Storage scale (Fisher z)
Prior PDF · normalnormal distribution. Storage scale (Fisher z). 95% CI ≈ [0.528, 0.608]; mean ≈ 0.568.0.4870.5270.5680.6090.650z0density

mean ≈ 0.568 · 95% CI ≈ [0.528, 0.608]

Reader scale (r)
Prior PDF · normalnormal distribution. Reader scale (r). 95% CI ≈ [0.485, 0.543]; mean ≈ 0.514.0.4540.4840.5140.5440.574r0density

mean ≈ 0.514 · 95% CI ≈ [0.485, 0.543]

Intervals

Confidence interval (95%) — uncertainty about the mean ρ
[0.48, 0.54]
Credibility interval (95%) — distribution of the true effect across settings (the Bayesian prior)
[0.48, 0.55]
I² (heterogeneity) — share of total variance from between-study differences
78%

The true effect is ~constant across settings — it generalizes.

SD_ρ≈0 — true effect is ~constant across settings; generalizes (observed-score scale until artifact correction, PRN-058)

Evidence provenance

published ρ=0.51 (k=2, high heterogeneity (I²=0.78)); no primary-deployment evidence yet

Sourceρ (r)Scope
Published literature0.51k = 2 · N = 12,751

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 | 0.568139, 0.0203577);
beta = pm.Normal("beta", mu=0.568139, sigma=0.0203577)
brms::prior(normal(0.568139, 0.0203577), class = "b")
# base R sample
rnorm(N, mean = 0.568139, sd = 0.0203577)
np.random.normal(loc=0.568139, scale=0.0203577, size=N)

Parameters

FamilyParameters
normalI2 = 0.7839, mu = 0.5681, sigma = 0.02036, r_mean = 0.5140, k_studies = 2.000, tau_squared = 0.0006537

Synthesis

Method
random_effects_meta
Informativeness
informative
Replication status
meta-analytic
k_studies
2
n_total
12,751
Last updated
2026-05-30T22:23:35.672Z

Quality distribution

GradeCount
A2
B0
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.