Table 2. Prior specification for Bayesian mixed-effects models.
| Parameter type | Parameter | Prior distribution | Rationale |
|---|---|---|---|
| Fixed effects (main models) | Regression coefficients (β) | Normal (0, 8) | Weakly informative, allowing broad plausible effects |
| Fixed effects (interaction models) | Regression coefficients (β) | Normal (0, 5) | Stronger shrinkage to reduce overfitting in higher-order terms |
| Intercept (current study)/ Intercept (pooled dataset) |
Intercept | Normal (75,30)/ Normal (50, 20) |
Midpoint matches the observed scale of outcomes in each dataset |
| Random effects SD | Subject-level SD | Student-t (3, 0, 10) | Weakly informative, allows heterogeneity across participants |
| Residual SD | σ | Student-t (3, 0, 10) | Weakly informative, constrains extreme variance |
β=regression coefficient; SD=standard deviation; σ=residual standard deviation. Normal (μ, σ) indicates a normal prior with mean μ and standard deviation σ; Student-t (ν, μ, σ) indicates a Student-t prior with degrees of freedom (ν), location (μ), and scale (σ). Subject-level SD represents between-participant variability captured by random effects. Priors were weakly informative unless otherwise noted.