Registry · Priors

construct.authentic_leadership predicts construct.work_engagement

normal · informative · 2 studies · N = 13,680

Distribution

Storage scale (Fisher z)
Prior PDF · normalnormal distribution. Storage scale (Fisher z). 95% CI ≈ [0.391, 0.617]; mean ≈ 0.504.0.2740.3890.5040.6190.734z0density

mean ≈ 0.504 · 95% CI ≈ [0.391, 0.617]

Reader scale (r)
Prior PDF · normalnormal distribution. Reader scale (r). 95% CI ≈ [0.377, 0.554]; mean ≈ 0.465.0.2850.3750.4650.5560.646r0density

mean ≈ 0.465 · 95% CI ≈ [0.377, 0.554]

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)
[0.33, 0.58]
I² (heterogeneity) — share of total variance from between-study differences
97%

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=0.47 (k=2, high heterogeneity (I²=0.97)); no primary-deployment evidence yet

Sourceρ (r)Scope
Published literature0.47k = 2 · N = 13,680

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 | 0.504177, 0.0575096);
beta = pm.Normal("beta", mu=0.504177, sigma=0.0575096)
brms::prior(normal(0.504177, 0.0575096), class = "b")
# base R sample
rnorm(N, mean = 0.504177, sd = 0.0575096)
np.random.normal(loc=0.504177, scale=0.0575096, size=N)

Parameters

FamilyParameters
normalI2 = 0.9678, mu = 0.5042, sigma = 0.05751, r_mean = 0.4654, k_studies = 2.000, tau_squared = 0.006404

Synthesis

Method
random_effects_meta
Informativeness
informative
Replication status
meta-analytic
k_studies
2
n_total
13,680
Last updated
2026-05-30T22:23:36.045Z

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.