construct.work_self_efficacy predicts construct.overall_job_performance
normal · informative · 2 studies · N = 21,666
Distribution
Historical evidence. This prior's contributing evidence is older than 15 years on average (centroid year 1998.1, ≈27.90000000000009 years old); treat the estimate as historical.
Intervals
- Confidence interval (95%) — uncertainty about the mean ρ
- [0.16, 0.46]
- Credibility interval (95%) — distribution of the true effect across settings (the Bayesian prior)
- [0.15, 0.48]
- I² (heterogeneity) — share of total variance from between-study differences
- 63% — substantial heterogeneity
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=0.32 (k=2, replication: meta-analytic); no primary-deployment evidence yet
| Source | ρ (r) | Scope |
|---|---|---|
| Published literature | 0.32 | k = 2 · N = 21,666 |
- replication: meta-analytic
- aging literature (freshness=0.28)
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 | 0.333542, 0.0866748);beta = pm.Normal("beta", mu=0.333542, sigma=0.0866748)brms::prior(normal(0.333542, 0.0866748), class = "b")# base R sample
rnorm(N, mean = 0.333542, sd = 0.0866748)np.random.normal(loc=0.333542, scale=0.0866748, size=N)Parameters
| Family | Parameters |
|---|---|
| normal | I2 = 0.6349, mu = 0.3335, sigma = 0.08667, r_mean = 0.3217, k_studies = 2.000, tau_squared = 0.008733, fisher_z_bias = -0.05781, r_mean_bare_bones = 0.3795 |
Synthesis
- Method
- random_effects_meta
- Informativeness
- informative
- Replication status
- meta-analytic
- k_studies
- 2
- n_total
- 21,666
- Last updated
- 2026-07-16T01:10:57.177Z
Quality distribution
| Grade | Count |
|---|---|
| A | 1 |
| B | 1 |
| 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.