Registry · Priors

construct.work_engagement predicts construct.organizational_commitment

normal · informative · 3 studies · N = 131,837

Distribution

Storage scale (Fisher z)
Prior PDF · normalnormal distribution. Storage scale (Fisher z). 95% CI ≈ [0.680, 0.761]; mean ≈ 0.721.0.6380.6790.7210.7620.803z0density

mean ≈ 0.721 · 95% CI ≈ [0.680, 0.761]

Reader scale (r)
Prior PDF · normalnormal distribution. Reader scale (r). 95% CI ≈ [0.592, 0.642]; mean ≈ 0.617.0.5660.5920.6170.6430.668r0density

mean ≈ 0.617 · 95% CI ≈ [0.592, 0.642]

Intervals

Confidence interval (95%) — uncertainty about the mean ρ
[0.59, 0.64]
Credibility interval (95%) — distribution of the true effect across settings (the Bayesian prior)
[0.57, 0.66]
I² (heterogeneity) — share of total variance from between-study differences
93%

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=0.62 (k=3, high heterogeneity (I²=0.93)); no primary-deployment evidence yet

Sourceρ (r)Scope
Published literature0.62k = 3 · N = 131,837

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 | 0.720522, 0.0206678);
beta = pm.Normal("beta", mu=0.720522, sigma=0.0206678)
brms::prior(normal(0.720522, 0.0206678), class = "b")
# base R sample
rnorm(N, mean = 0.720522, sd = 0.0206678)
np.random.normal(loc=0.720522, scale=0.0206678, size=N)

Parameters

FamilyParameters
normalI2 = 0.9310, mu = 0.7205, sigma = 0.02067, r_mean = 0.6172, k_studies = 3.000, tau_squared = 0.001171

Synthesis

Method
random_effects_meta
Informativeness
informative
Replication status
meta-analytic
k_studies
3
n_total
131,837
Last updated
2026-05-29T15:21:17.978Z

Quality distribution

GradeCount
A3
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.