construct.turnover_intention predicts construct.voluntary_turnover
normal · informative · 3 studies · N = 136,687
Distribution
Intervals
- Confidence interval (95%) — uncertainty about the mean ρ
- [0.32, 0.62]
- Credibility interval (95%) — distribution of the true effect across settings (the Bayesian prior)
- [0.20, 0.69]
- 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=0.48 (k=3, high heterogeneity (I²=1.00)); no primary-deployment evidence yet
| Source | ρ (r) | Scope |
|---|---|---|
| Published literature | 0.48 | k = 3 · N = 136,687 |
- high heterogeneity (I²=1.00)
- replication: meta-analytic
- aging literature (freshness=0.47)
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 | 0.525238, 0.0994798);beta = pm.Normal("beta", mu=0.525238, sigma=0.0994798)brms::prior(normal(0.525238, 0.0994798), class = "b")# base R sample
rnorm(N, mean = 0.525238, sd = 0.0994798)np.random.normal(loc=0.525238, scale=0.0994798, size=N)Parameters
| Family | Parameters |
|---|---|
| normal | I2 = 0.9989, mu = 0.5252, sigma = 0.09948, r_mean = 0.4817, k_studies = 3.000, tau_squared = 0.02700 |
Synthesis
- Method
- random_effects_meta
- Informativeness
- informative
- Replication status
- meta-analytic
- k_studies
- 3
- n_total
- 136,687
- Last updated
- 2026-05-31T01:07:48.040Z
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.