Registry · Priors

construct.general_mental_ability_gma predicts construct.employee_performance

normal · weakly_informative · 4 studies · N = 59,513

Distribution

Weakly informative prior. This prior is weakly informative. It will nudge your posterior but won't overwhelm it; expect data to do most of the work in modest samples.

Intervals

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

[0.19, 0.54]

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

[0.02, 0.65]

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

100%

The true effect varies across settings — moderators likely matter.

SD_ρ>0 — true effect varies across settings; likely moderated (observed-score scale until artifact correction, PRN-058)

Evidence provenance

published ρ=0.38 (k=4, high heterogeneity (I²=1.00)); no primary-deployment evidence yet

• high heterogeneity (I²=1.00)
• replication: meta-analytic

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 | 0.397231, 0.104429);

beta = pm.Normal("beta", mu=0.397231, sigma=0.104429)

brms::prior(normal(0.397231, 0.104429), class = "b")

# base R sample
rnorm(N, mean = 0.397231, sd = 0.104429)

np.random.normal(loc=0.397231, scale=0.104429, size=N)

Parameters

Synthesis

Method

random_effects_meta

Informativeness

weakly_informative

Replication status

meta-analytic

k_studies

4

n_total

59,513

Last updated

2026-05-30T11:46:57.783Z

Quality distribution

Contributing effect sizes

• effect.2a0e9697d5a6819c
• effect.d4e172e5cfc1f5a2
• effect.1d77735bf95df79b
• effect.f7af2afbd436a7ec

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