construct.person_job_fit predicts construct.job_satisfaction
normal · informative · 2 studies · N = 13,010
Distribution
Intervals
- Confidence interval (95%) — uncertainty about the mean ρ
- [0.55, 0.57]
- Credibility interval (95%) — distribution of the true effect across settings (the Bayesian prior)
- [0.56, 0.56]
- I² (heterogeneity) — share of total variance from between-study differences
- 0%
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=0.56 (k=2, replication: meta-analytic); no primary-deployment evidence yet
| Source | ρ (r) | Scope |
|---|---|---|
| Published literature | 0.56 | k = 2 · N = 13,010 |
- 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.
target += normal_lpdf(beta | 0.632833, 0.00875142);beta = pm.Normal("beta", mu=0.632833, sigma=0.00875142)brms::prior(normal(0.632833, 0.00875142), class = "b")# base R sample
rnorm(N, mean = 0.632833, sd = 0.00875142)np.random.normal(loc=0.632833, scale=0.00875142, size=N)Parameters
| Family | Parameters |
|---|---|
| normal | I2 = 0.000, mu = 0.6328, sigma = 0.008751, r_mean = 0.5600, k_studies = 2.000, tau_squared = 0.000 |
Synthesis
- Method
- random_effects_meta
- Informativeness
- informative
- Replication status
- meta-analytic
- k_studies
- 2
- n_total
- 13,010
- Last updated
- 2026-05-30T22:23:32.514Z
Quality distribution
| Grade | Count |
|---|---|
| A | 2 |
| 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.