TABLE 4.

Predictiveness of different factors (i.e., ml, g, rl, and d) regarding the criterion cogIll in two different frequentist models (with and without interactions).

Frequentist Model	Estimate	SE	p	Explained variance
Without Interactions				R2Marginal = 0.054; R2Conditional = 0.040
γ00	−2.2	0.575	< 0.001
ml	0.067	0.006	< 0.001
g	0.039	0.012	0.001
rl	−0.028	0.014	0.04
d	–1.074	0.804	0.182
With Interactions				R2Marginal = 0.107; R2Conditional = 0.348
γ00	−3.039	0.615	< 0.001
ml	0.087	0.008	< 0.001
g	0.046	0.016	0.005
rl	0.022	0.018	0.234
d	0.822	0.867	0.343
ml × d	−0.042	0.012	< 0.001
g × d	–0.015	0.024	0.536
rl × d	–0.124	0.027	< 0.001

Model fit: CFI: 0.990, RMSEA: 0.017.

Estimate, Estimated unstandardized parameter value; SE, Standard error of the parameter estimate; df, Degrees of freedom; p, Probability of committing a Type I Error; γ₀₀, Intercept of the additive predictor term; R²_Marginal, Variance explained by fixed effects; R²_Conditional, Variance explained by both fixed and random effects.

Significant (direct or interaction) effects (p < 0.05) are written in bold. Corresponding Bayesian models as well as models without the Linda task can be found in Appendix Tables A1, A2.