construct.conscientiousness predicts construct.counterproductive_work_behaviours
normal · informative · 3 studies · N = 17,652
Distribution
Intervals
- Confidence interval (95%) — uncertainty about the mean ρ
- [-0.39, -0.32]
- Credibility interval (95%) — distribution of the true effect across settings (the Bayesian prior)
- [-0.40, -0.32]
- I² (heterogeneity) — share of total variance from between-study differences
- 48% — moderate heterogeneity
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=-0.36 (k=3, replication: meta-analytic); no primary-deployment evidence yet
| Source | ρ (r) | Scope |
|---|---|---|
| Published literature | -0.36 | k = 3 · N = 17,652 |
- 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
Drop this prior straight into your model. Snippets generated from the synthesized distribution + parameters.
target += normal_lpdf(beta | -0.373174, 0.0194204);beta = pm.Normal("beta", mu=-0.373174, sigma=0.0194204)brms::prior(normal(-0.373174, 0.0194204), class = "b")# base R sample
rnorm(N, mean = -0.373174, sd = 0.0194204)np.random.normal(loc=-0.373174, scale=0.0194204, size=N)Parameters
| Family | Parameters |
|---|---|
| normal | I2 = 0.4814, mu = -0.3732, sigma = 0.01942, r_mean = -0.3568, k_studies = 3.000, tau_squared = 0.0005377, fisher_z_bias = 0.01082, r_mean_bare_bones = -0.3676 |
Synthesis
- Method
- random_effects_meta
- Informativeness
- informative
- Replication status
- meta-analytic
- k_studies
- 3
- n_total
- 17,652
- Last updated
- 2026-07-16T01:07:10.169Z
Quality distribution
| Grade | Count |
|---|---|
| A | 2 |
| 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).
Interpersonal deviance, organizational deviance, and their common correlates: A review and meta-analysis.
Predicting counterproductive work behaviors: A meta-analysis of their relationship with individual and situational factors
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.