Registry · Priors

construct.general_mental_ability_gma predicts construct.training_performance

normal · informative · 2 studies · N = 15,305

Distribution

Storage scale (Fisher z)
Prior PDF · normalnormal distribution. Storage scale (Fisher z). 95% CI ≈ [0.445, 0.693]; mean ≈ 0.569.0.3150.4420.5690.6950.822z0density

mean ≈ 0.569 · 95% CI ≈ [0.445, 0.693]

Reader scale (r)
Prior PDF · normalnormal distribution. Reader scale (r). 95% CI ≈ [0.423, 0.606]; mean ≈ 0.514.0.3280.4210.5140.6070.701r0density

mean ≈ 0.514 · 95% CI ≈ [0.423, 0.606]

Intervals

Confidence interval (95%) — uncertainty about the mean ρ
[0.42, 0.60]
Credibility interval (95%) — distribution of the true effect across settings (the Bayesian prior)
[0.38, 0.63]
I² (heterogeneity) — share of total variance from between-study differences
98%

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=0.51 (k=2, high heterogeneity (I²=0.98)); no primary-deployment evidence yet

Sourceρ (r)Scope
Published literature0.51k = 2 · N = 15,305

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 | 0.568675, 0.0632975);
beta = pm.Normal("beta", mu=0.568675, sigma=0.0632975)
brms::prior(normal(0.568675, 0.0632975), class = "b")
# base R sample
rnorm(N, mean = 0.568675, sd = 0.0632975)
np.random.normal(loc=0.568675, scale=0.0632975, size=N)

Parameters

FamilyParameters
normalI2 = 0.9761, mu = 0.5687, sigma = 0.06330, r_mean = 0.5144, k_studies = 2.000, tau_squared = 0.007823

Synthesis

Method
random_effects_meta
Informativeness
informative
Replication status
meta-analytic
k_studies
2
n_total
15,305
Last updated
2026-05-30T11:46:58.263Z

Quality distribution

GradeCount
A2
B0
C0
D0

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.