Registry · Priors

construct.collective_turnover predicts construct.organizational_performance

normal · informative · 2 studies · N = 145,009

Distribution

Intervals

Confidence interval (95%) — uncertainty about the mean ρ

[-0.21, 0.03]

Credibility interval (95%) — distribution of the true effect across settings (the Bayesian prior)

[-0.25, 0.08]

I² (heterogeneity) — share of total variance from between-study differences

100%

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=-0.09 (k=2, high heterogeneity (I²=1.00)); no primary-deployment evidence yet

• high heterogeneity (I²=1.00)
• replication: meta-analytic

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

target += normal_lpdf(beta | -0.0907058, 0.0605656);

beta = pm.Normal("beta", mu=-0.0907058, sigma=0.0605656)

brms::prior(normal(-0.0907058, 0.0605656), class = "b")

# base R sample
rnorm(N, mean = -0.0907058, sd = 0.0605656)

np.random.normal(loc=-0.0907058, scale=0.0605656, size=N)

Parameters

Synthesis

Method

random_effects_meta

Informativeness

informative

Replication status

meta-analytic

k_studies

2

n_total

145,009

Last updated

2026-05-30T12:06:17.944Z

Quality distribution

Contributing effect sizes

• effect.ffffa606e720df00
• effect.194ebd65e054bce4

Effect-size detail pages land with a later sub-ticket; for now, ids link to the filtered list. Browse all rows via /registry/effects.