Registry · Priors

construct.person_job_fit predicts construct.task_performance

normal · informative · 2 studies · N = 4,798

Distribution

Storage scale (Fisher z)
Prior PDF · normalnormal distribution. Storage scale (Fisher z). 95% CI ≈ [0.0953, 0.249]; mean ≈ 0.172.0.01540.09370.1720.2500.328z0density

mean ≈ 0.172 · 95% CI ≈ [0.0953, 0.249]

Reader scale (r)
Prior PDF · normalnormal distribution. Reader scale (r). 95% CI ≈ [0.0958, 0.245]; mean ≈ 0.170.0.01830.09430.1700.2460.322r0density

mean ≈ 0.170 · 95% CI ≈ [0.0958, 0.245]

Historical evidence. This prior's contributing evidence is older than 15 years on average (centroid year 2005, ≈21 years old); treat the estimate as historical.

Intervals

Confidence interval (95%) — uncertainty about the mean ρ
[0.09, 0.24]
Credibility interval (95%) — distribution of the true effect across settings (the Bayesian prior)
[0.08, 0.26]
I² (heterogeneity) — share of total variance from between-study differences
83% — considerable heterogeneity; moderators likely dominate

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=0.17 (k=2, high heterogeneity (I²=0.83)); no primary-deployment evidence yet

Sourceρ (r)Scope
Published literature0.17k = 2 · N = 4,798

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 | 0.17196, 0.0391346);
beta = pm.Normal("beta", mu=0.17196, sigma=0.0391346)
brms::prior(normal(0.17196, 0.0391346), class = "b")
# base R sample
rnorm(N, mean = 0.17196, sd = 0.0391346)
np.random.normal(loc=0.17196, scale=0.0391346, size=N)

Parameters

FamilyParameters
normalI2 = 0.8328, mu = 0.1720, sigma = 0.03913, r_mean = 0.1703, k_studies = 2.000, tau_squared = 0.002158, fisher_z_bias = 0.005853, r_mean_bare_bones = 0.1644

Synthesis

Method
random_effects_meta
Informativeness
informative
Replication status
meta-analytic
k_studies
2
n_total
4,798
Last updated
2026-07-16T01:06:35.018Z

Quality distribution

GradeCount
A1
B1
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.