Registry · Priors

construct.competence predicts construct.task_performance

normal · informative · 2 studies · N = 35,909

Distribution

Storage scale (Fisher z)
Prior PDF · normalnormal distribution. Storage scale (Fisher z). 95% CI ≈ [0.370, 0.438]; mean ≈ 0.404.0.3340.3690.4040.4390.474z0density

mean ≈ 0.404 · 95% CI ≈ [0.370, 0.438]

Reader scale (r)
Prior PDF · normalnormal distribution. Reader scale (r). 95% CI ≈ [0.354, 0.412]; mean ≈ 0.383.0.3240.3530.3830.4130.443r0density

mean ≈ 0.383 · 95% CI ≈ [0.354, 0.412]

Intervals

Confidence interval (95%) — uncertainty about the mean ρ
[0.35, 0.41]
Credibility interval (95%) — distribution of the true effect across settings (the Bayesian prior)
[0.34, 0.42]
I² (heterogeneity) — share of total variance from between-study differences
82%

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=0.38 (k=2, high heterogeneity (I²=0.82)); no primary-deployment evidence yet

Sourceρ (r)Scope
Published literature0.38k = 2 · N = 35,909

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 | 0.4038, 0.0174704);
beta = pm.Normal("beta", mu=0.4038, sigma=0.0174704)
brms::prior(normal(0.4038, 0.0174704), class = "b")
# base R sample
rnorm(N, mean = 0.4038, sd = 0.0174704)
np.random.normal(loc=0.4038, scale=0.0174704, size=N)

Parameters

FamilyParameters
normalI2 = 0.8204, mu = 0.4038, sigma = 0.01747, r_mean = 0.3832, k_studies = 2.000, tau_squared = 0.0005090

Synthesis

Method
random_effects_meta
Informativeness
informative
Replication status
meta-analytic
k_studies
2
n_total
35,909
Last updated
2026-05-30T16:21:36.173Z

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.