construct.affective_commitment predicts construct.turnover_intention
normal · weakly_informative · 1 studies · N = 16,906
Distribution
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.
Historical evidence. This prior's contributing evidence is older than 15 years on average (centroid year 2002, ≈24 years old); treat the estimate as historical.
Intervals
- Confidence interval (95%) — uncertainty about the mean ρ
- [-0.57, -0.55]
- Credibility interval (95%) — distribution of the true effect across settings (the Bayesian prior)
- — needs ≥2 studies to estimate (k = 1)
- I² (heterogeneity) — share of total variance from between-study differences
- — needs ≥2 studies to estimate
k<2 — between-study heterogeneity not estimable; credibility interval / generalization not assessed
Evidence provenance
published ρ=-0.56 (k=1, replication: meta-analytic); no primary-deployment evidence yet
| Source | ρ (r) | Scope |
|---|---|---|
| Published literature | -0.56 | k = 1 · N = 16,906 |
- replication: meta-analytic
- aging literature (freshness=0.30)
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 | -0.632833, 0.00769163);beta = pm.Normal("beta", mu=-0.632833, sigma=0.00769163)brms::prior(normal(-0.632833, 0.00769163), class = "b")# base R sample
rnorm(N, mean = -0.632833, sd = 0.00769163)np.random.normal(loc=-0.632833, scale=0.00769163, size=N)Parameters
| Family | Parameters |
|---|---|
| normal | mu = -0.6328, sigma = 0.007692, r_mean = -0.5600, k_studies = 1.000, tau_squared = 0.000 |
Synthesis
- Method
- single_study
- Informativeness
- weakly_informative
- Replication status
- meta-analytic
- k_studies
- 1
- n_total
- 16,906
- Last updated
- 2026-07-16T01:09:32.373Z
Quality distribution
| Grade | Count |
|---|---|
| A | 1 |
| B | 0 |
| C | 0 |
| D | 0 |
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.