Table 1.

Regression paths from the path model of temperament composites predicting psychopathology factors

	Bifactor model							Correlated factors model
Factor/predictor	β	b	SE	z	p	LL	UL	β	b	SE	z	p	LL	UL
p factor
Negative affect	−0.11	−0.13	0.11	−1.11	0.269	−0.35	0.10
Positive affect	−0.04	−0.05	0.12	−0.43	0.667	−0.30	0.19
Motor activity	0.44	0.52	0.11	4.80	0.000	0.31	0.74
Maternal ethnicity	0.13	0.15	0.20	0.76	0.447	−0.24	0.54
Maternal education	−0.05	−0.06	0.13	−0.45	0.654	−0.31	0.19
Gender	−0.36	−0.43	0.18	−2.35	0.019	−0.79	−0.07
Externalizing factor
Negative affect	−0.07	−0.08	0.15	−0.53	0.596	−0.37	0.22	−0.12	−0.18	0.11	−1.56	0.119	−0.40	0.05
Positive affect	−0.04	−0.04	0.15	−0.28	0.777	−0.33	0.25	−0.06	−0.09	0.12	−0.72	0.469	−0.32	0.15
Motor activity	0.06	0.07	0.17	0.39	0.694	−0.26	0.39	0.37	0.51	0.10	5.17	0.000	0.32	0.70
Maternal ethnicity	−0.16	−0.18	0.25	−0.72	0.470	−0.66	0.31	0.04	0.09	0.20	0.43	0.668	−0.31	0.48
Maternal education	−0.20	−0.22	0.16	−1.43	0.152	−0.53	0.08	−0.09	−0.14	0.12	−1.22	0.224	−0.38	0.09
Gender	−0.22	−0.24	0.24	−1.02	0.309	−0.71	0.23	−0.21	−0.47	0.17	−2.79	0.005	−0.79	−0.14
Internalizing factor
Negative affect	−0.19	−0.26	0.17	−1.52	0.128	−0.60	0.08	−0.16	−0.25	0.14	−1.83	0.067	−0.52	0.02
Positive affect	−0.37	−0.51	0.19	−2.63	0.009	−0.88	−0.13	−0.24	−0.35	0.15	−2.40	0.016	−0.64	−0.07
Motor activity	−0.08	−0.11	0.18	−0.61	0.540	−0.46	0.24	0.27	0.37	0.12	3.09	0.002	0.13	0.60
Maternal ethnicity	−0.05	−0.06	0.31	−0.20	0.842	−0.67	0.55	0.04	0.08	0.22	0.39	0.697	−0.34	0.51
Maternal education	−0.37	−0.50	0.19	−2.65	0.008	−0.87	−0.13	−0.23	−0.35	0.14	−2.40	0.016	−0.63	−0.06
Gender	0.40	0.55	0.31	1.77	0.077	−0.06	1.16	0.08	0.17	0.19	0.92	0.355	−0.19	0.54

Note: p factor = general psychopathology factor, β = standardized estimates, b = unstandardized estimates, LL = lower limit of 95% confidence interval, UL = upper limit of 95% confidence interval. Bold estimates and p values showed statistical significance with adjustment for multiple comparisons (q < .05; FDR). Albeit the analysis with the bifactor model was performed following the methods recommended by Koch et al. (2018), the table is presented as a traditional regression analysis to simplify its presentation.