Registry · Priors

construct.person_organization_fit predicts construct.organizational_citizenship_behavior_ocb

normal · informative · 2 studies · N = 2,172

Distribution

Storage scale (Fisher z)
Prior PDF · normalnormal distribution. Storage scale (Fisher z). 95% CI ≈ [0.233, 0.317]; mean ≈ 0.275.0.1890.2320.2750.3180.360z0density

mean ≈ 0.275 · 95% CI ≈ [0.233, 0.317]

Reader scale (r)
Prior PDF · normalnormal distribution. Reader scale (r). 95% CI ≈ [0.229, 0.307]; mean ≈ 0.268.0.1890.2280.2680.3080.347r0density

mean ≈ 0.268 · 95% CI ≈ [0.229, 0.307]

Historical evidence. This prior's contributing evidence is older than 15 years on average (centroid year 2005.03, ≈20.970000000000027 years old); treat the estimate as historical.

Intervals

Confidence interval (95%) — uncertainty about the mean ρ
[0.23, 0.31]
Credibility interval (95%) — distribution of the true effect across settings (the Bayesian prior)
[0.27, 0.27]
I² (heterogeneity) — share of total variance from between-study differences
0% — 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=0.27 (k=2, replication: meta-analytic); no primary-deployment evidence yet

Sourceρ (r)Scope
Published literature0.27k = 2 · N = 2,172

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 | 0.274827, 0.0213736);
beta = pm.Normal("beta", mu=0.274827, sigma=0.0213736)
brms::prior(normal(0.274827, 0.0213736), class = "b")
# base R sample
rnorm(N, mean = 0.274827, sd = 0.0213736)
np.random.normal(loc=0.274827, scale=0.0213736, size=N)

Parameters

FamilyParameters
normalI2 = 0.000, mu = 0.2748, sigma = 0.02137, r_mean = 0.2681, k_studies = 2.000, tau_squared = 0.000, fisher_z_bias = -0.0009157, r_mean_bare_bones = 0.2690

Synthesis

Method
random_effects_meta
Informativeness
informative
Replication status
meta-analytic
k_studies
2
n_total
2,172
Last updated
2026-07-16T01:06:22.715Z

Quality distribution

GradeCount
A1
B1
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.