Registry · Priors

construct.structured_employment_interviews predicts construct.overall_job_performance

normal · informative · 2 studies · N = 12,897

Distribution

Storage scale (Fisher z)
Prior PDF · normalnormal distribution. Storage scale (Fisher z). 95% CI ≈ [0.455, 0.489]; mean ≈ 0.472.0.4370.4540.4720.4900.507z0density

mean ≈ 0.472 · 95% CI ≈ [0.455, 0.489]

Reader scale (r)
Prior PDF · normalnormal distribution. Reader scale (r). 95% CI ≈ [0.426, 0.454]; mean ≈ 0.440.0.4110.4260.4400.4540.468r0density

mean ≈ 0.440 · 95% CI ≈ [0.426, 0.454]

Historical evidence. This prior's contributing evidence is older than 15 years on average (centroid year 1994.22, ≈31.779999999999973 years old); treat the estimate as historical.

Intervals

Confidence interval (95%) — uncertainty about the mean ρ
[0.43, 0.45]
Credibility interval (95%) — distribution of the true effect across settings (the Bayesian prior)
[0.44, 0.44]
I² (heterogeneity) — share of total variance from between-study differences
0% — 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=0.44 (k=2, replication: meta-analytic); no primary-deployment evidence yet

Sourceρ (r)Scope
Published literature0.44k = 2 · N = 12,897

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 | 0.472041, 0.00878953);
beta = pm.Normal("beta", mu=0.472041, sigma=0.00878953)
brms::prior(normal(0.472041, 0.00878953), class = "b")
# base R sample
rnorm(N, mean = 0.472041, sd = 0.00878953)
np.random.normal(loc=0.472041, scale=0.00878953, size=N)

Parameters

FamilyParameters
normalI2 = 0.000, mu = 0.4720, sigma = 0.008790, r_mean = 0.4398, k_studies = 2.000, tau_squared = 0.000, fisher_z_bias = -0.00007535, r_mean_bare_bones = 0.4399

Synthesis

Method
random_effects_meta
Informativeness
informative
Replication status
meta-analytic
k_studies
2
n_total
12,897
Last updated
2026-07-16T01:10:38.829Z

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.