Registry · Priors

construct.performance_feedback predicts construct.overall_job_performance

normal · informative · 3 studies · N = 85,055

Distribution

Intervals

Confidence interval (95%) — uncertainty about the mean ρ

[0.31, 0.55]

Credibility interval (95%) — distribution of the true effect across settings (the Bayesian prior)

[0.38, 0.50]

I² (heterogeneity) — share of total variance from between-study differences

9% — 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=3, replication: meta-analytic); no primary-deployment evidence yet

• replication: meta-analytic
• aging literature (freshness=0.43)

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

target += normal_lpdf(beta | 0.474327, 0.0759346);

beta = pm.Normal("beta", mu=0.474327, sigma=0.0759346)

brms::prior(normal(0.474327, 0.0759346), class = "b")

# base R sample
rnorm(N, mean = 0.474327, sd = 0.0759346)

np.random.normal(loc=0.474327, scale=0.0759346, size=N)

Parameters

Synthesis

Method

random_effects_meta

Informativeness

informative

Replication status

meta-analytic

k_studies

3

n_total

85,055

Last updated

2026-07-16T01:10:45.067Z

Quality distribution

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.6b354cdd11d8010b
• effect.abb60b3f8f2ea7ac
• effect.d8a9baeb7c183de8

Effect-size detail pages land with a later sub-ticket; for now, ids link to the filtered list. Browse all rows via /registry/effects.