Table 4.

Latent growth models for preference for solitude.

	Unstandardized results			Standardized results
	Estimate	SE	p	Estimate	SE	p
Model for the urban group (n = 326)xs
Intercept (I)	2.18 (0.475)	0.09	<0.001	2.86	0.29	<0.001
Slope (S)	0.16 (0.071)	0.05	0.004	0.42	0.15	0.006
I-S covariance	−0.08	0.07	0.242	−0.28	0.17	0.099
Gender→ I	0.06	0.11	0.587	0.04	0.07	0.589
Gender→ S	−0.00	0.07	0.974	−0.00	0.10	0.974
Model fit: χ2 (2) = 0.218, p = 0.897, CFI = 1.000, TLI = 1.022, RMSEA = 0.000
Model for the rural group (n = 449)
Intercept (I)	2.21 (0.581)	0.07	<0.001	3.18	0.29	<0.001
Slope (S)	0.12 (0.140)	0.05	0.007	0.44	0.21	0.031
I-S covariance	−0.04	0.05	0.362	−0.23	0.18	0.206
Gender→ I	0.14	0.09	0.109	0.10	0.06	0.108
Gender→ S	−0.11	0.05	0.044	−0.20	0.11	0.070
Model fit: χ2 (2) = 0.486, p = 0.784; CFI = 1.000, TLI = 1.022, RMSEA = 0.000
Model examining location as a predictor of the growth curve (N = 775)
Intercept (I)	2.19 (0.518)	0.05	<0.001	3.04	0.21	<0.001
Slope (S)	0.14 (0.102)	0.04	<0.001	0.43	0.12	<0.001
I-S covariance	−0.06	0.04	0.148	−0.25	0.12	0.046
Location → I	−0.05	0.04	0.270	−0.07	0.06	0.268
Location → S	0.07	0.03	0.010	0.22	0.09	0.013
Gender→ I	0.10	0.07	0.156	0.07	0.05	0.158
Gender→ S	−0.06	0.05	0.207	−0.09	0.07	0.208
Location × Gender→ I	−0.04	0.07	0.598	−0.04	0.07	0.598
Location × Gender→ S	0.05	0.05	0.242	0.11	0.10	0.256
Model fit: χ2 (4) = 0.683, p = 0.953; CFI = 1.000, TLI = 1.000, RMSEA = 0.000

Location coded as Urban = 1, Rural = −1. Gender coded as Boy = 0, Girl = 1. Residual variance of the intercepts and slopes are reported in parenthesis. Residual variance of the intercept and slope did not differ between the urban and the rural groups.