|
LGM model tested
|
Δχ2
|
|---|
|
χ2
|
df
|
p-value
|
CFI
|
ΔCFI
|
AIC
|
|---|
|
Interest
| | | | | | |
|
Intercept only
|
188.428**
|
16
| |
0.749
| |
22,230
|
|
Linear (vs intercept)
|
29.092**
|
13
|
0.000
|
0.977
|
0.228
|
22,027
|
|
Quadratic (vs linear)
|
29.330**
|
12
|
0.626
|
0.975
|
0.002
|
22,029
|
|
Cubic (vs linear)
|
31.878**
|
11
|
0.248
|
0.970
|
0.007
|
22,035
|
|
Anxiety
| | | | | | |
|
Intercept only
|
98.381**
|
16
| |
0.784
| |
25,011
|
|
Linear (vs intercept)
|
35.275**
|
13
|
0.000
|
0.942
|
0.158
|
24,931
|
|
Quadratic (vs linear)
|
37.383**
|
12
|
0.147
|
0.933
|
0.009
|
24,937
|
|
Cubic (vs linear)
|
35.520**
|
11
|
0.885
|
0.936
|
0.003
|
24,938
|
|
Piecewise 1 (vs linear)a
|
28.045**
|
13
|
–
|
0.961
|
–
|
24,921
|
|
Piecewise 2 (vs piecewise 1)b
|
23.618*
|
13
|
–
|
0.972
|
–
|
24,915
|
- Both quadratic models did not converge due to negative variance on linear slope, resolved by fixing the variance to zero. Both cubic models did not converge, resolved by holding the linear and quadratic variances to zero. Italicised entries indicate improved fit
- **p < .01, * p < .05
- aPiecewise model with linear slope1 at T1–T5 and slope2 at T6 = 0
- bPiecewise model with slope1 at T1 and T2 = 0; linear slope2 at T3–T5 and slope 3 at T6 = 0
