Registry · Priors

construct.psychological_capital_psycap predicts construct.job_satisfaction

normal · weakly_informative · 2 studies · N = 3,173

Distribution

Storage scale (Fisher z)
Prior PDF · normalnormal distribution. Storage scale (Fisher z). 95% CI ≈ [0.476, 0.921]; mean ≈ 0.698.0.2450.4720.6980.9251.15z0density

mean ≈ 0.698 · 95% CI ≈ [0.476, 0.921]

Reader scale (r)
Prior PDF · normalnormal distribution. Reader scale (r). 95% CI ≈ [0.462, 0.745]; mean ≈ 0.603.0.3150.4590.6030.7480.892r0density

mean ≈ 0.603 · 95% CI ≈ [0.462, 0.745]

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
[0.44, 0.73]
Credibility interval (95%) — distribution of the true effect across settings (the Bayesian prior)
[0.39, 0.76]
I² (heterogeneity) — share of total variance from between-study differences
81% — considerable heterogeneity; moderators likely dominate

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=0.60 (k=2, high heterogeneity (I²=0.81)); no primary-deployment evidence yet

Sourceρ (r)Scope
Published literature0.60k = 2 · N = 3,173

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 | 0.698444, 0.113353);
beta = pm.Normal("beta", mu=0.698444, sigma=0.113353)
brms::prior(normal(0.698444, 0.113353), class = "b")
# base R sample
rnorm(N, mean = 0.698444, sd = 0.113353)
np.random.normal(loc=0.698444, scale=0.113353, size=N)

Parameters

FamilyParameters
normalI2 = 0.8059, mu = 0.6984, sigma = 0.1134, r_mean = 0.6034, k_studies = 2.000, tau_squared = 0.02142, fisher_z_bias = 0.06113, r_mean_bare_bones = 0.5423

Synthesis

Method
random_effects_meta
Informativeness
weakly_informative
Replication status
meta-analytic
k_studies
2
n_total
3,173
Last updated
2026-07-16T01:06:59.002Z

Quality distribution

GradeCount
A2
B0
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.