Registry · Priors

construct.person_organization_fit predicts construct.turnover_intention

normal · informative · 3 studies · N = 34,376

Distribution

Storage scale (Fisher z)

mean ≈ -0.355 · 95% CI ≈ [-0.408, -0.303]

Reader scale (r)

mean ≈ -0.341 · 95% CI ≈ [-0.387, -0.295]

Historical evidence. This prior's contributing evidence is older than 15 years on average (centroid year 2004.99, ≈21.00999999999999 years old); treat the estimate as historical.

Intervals

Confidence interval (95%) — uncertainty about the mean ρ: [-0.39, -0.29]
Credibility interval (95%) — distribution of the true effect across settings (the Bayesian prior): [-0.39, -0.29]
I² (heterogeneity) — share of total variance from between-study differences: 13%

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=-0.34 (k=3, replication: meta-analytic); no primary-deployment evidence yet

Source	ρ (r)	Scope
Published literature	-0.34	k = 3 · N = 34,376

replication: meta-analytic
aging literature (freshness=0.37)

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.

StanPyMCbrmsRNumPy

target += normal_lpdf(beta | -0.355473, 0.0265723);

beta = pm.Normal("beta", mu=-0.355473, sigma=0.0265723)

brms::prior(normal(-0.355473, 0.0265723), class = "b")

# base R sample
rnorm(N, mean = -0.355473, sd = 0.0265723)

np.random.normal(loc=-0.355473, scale=0.0265723, size=N)

Parameters

Family	Parameters
normal	I2 = 0.1349, mu = -0.3555, sigma = 0.02657, r_mean = -0.3412, k_studies = 3.000, tau_squared = 0.0007833

Synthesis

Method: random_effects_meta
Informativeness: informative
Replication status: meta-analytic
k_studies: 3
n_total: 34,376
Last updated: 2026-05-30T22:23:33.703Z

Quality distribution

Grade	Count
A	3
B	0
C	0
D	0

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.