Registry · Priors

construct.procedural_justice predicts construct.turnover_intention

normal · informative · 2 studies · N = 24,323

Distribution

Storage scale (Fisher z)
Prior PDF · normalnormal distribution. Storage scale (Fisher z). 95% CI ≈ [-0.549, -0.426]; mean ≈ -0.488.-0.613-0.550-0.488-0.425-0.362z0density

mean ≈ -0.488 · 95% CI ≈ [-0.549, -0.426]

Reader scale (r)
Prior PDF · normalnormal distribution. Reader scale (r). 95% CI ≈ [-0.501, -0.403]; mean ≈ -0.452.-0.552-0.502-0.452-0.402-0.353r0density

mean ≈ -0.452 · 95% CI ≈ [-0.501, -0.403]

Historical evidence. This prior's contributing evidence is older than 15 years on average (centroid year 2001.09, ≈24.910000000000082 years old); treat the estimate as historical.

Intervals

Confidence interval (95%) — uncertainty about the mean ρ
[-0.50, -0.40]
Credibility interval (95%) — distribution of the true effect across settings (the Bayesian prior)
[-0.50, -0.40]
I² (heterogeneity) — share of total variance from between-study differences
17% — studies largely agree

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=-0.45 (k=2, replication: meta-analytic); no primary-deployment evidence yet

Sourceρ (r)Scope
Published literature-0.45k = 2 · N = 24,323

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 | -0.487536, 0.0313073);
beta = pm.Normal("beta", mu=-0.487536, sigma=0.0313073)
brms::prior(normal(-0.487536, 0.0313073), class = "b")
# base R sample
rnorm(N, mean = -0.487536, sd = 0.0313073)
np.random.normal(loc=-0.487536, scale=0.0313073, size=N)

Parameters

FamilyParameters
normalI2 = 0.1708, mu = -0.4875, sigma = 0.03131, r_mean = -0.4523, k_studies = 2.000, tau_squared = 0.001034, fisher_z_bias = 0.007554, r_mean_bare_bones = -0.4598

Synthesis

Method
random_effects_meta
Informativeness
informative
Replication status
meta-analytic
k_studies
2
n_total
24,323
Last updated
2026-07-16T01:08:18.567Z

Quality distribution

GradeCount
A2
B0
C0
D0

Source articles

The research this prior is synthesized from — each is a full dossier (findings, the models it informs, and what the literature says).

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.