|
Model
|
Log Likelihood
|
AIC
|
BIC
|
SABIC
|
Entropy
|
Smallest Class %
|
LMR p-value
|
LMR meaning
|
|---|
|
1
|
− 6682.848
|
13,385.696
|
13,430.619
|
13,398.868
| | |
–
|
–
|
|
2
|
− 5908.942
|
11,849.884
|
11,921.759
|
11,870.959
|
0.987
|
0.19091
|
< 0.001
|
2> 1
|
|
3
|
− 5707.847
|
11,459.694
|
11,558.523
|
11,488.673
|
0.989
|
0.09545
|
< 0.001
|
3> 2
|
|
4
|
− 5554.458
|
11,164.915
|
11,290.698
|
11,201.797
|
0.994
|
0.08182
|
< 0.001
|
4> 3
|
|
5
|
− 5442.434
|
10,952.868
|
11,105.604
|
10,997.653
|
0.980
|
0.02424
|
0.139
|
5< 4
|
- n = 660; The LMR test compares the current model to a model with k −1 profiles
- AIC Akaike’s Information Criterion, BIC Bayesian Information Criterion, SABIC Sample-Adjusted BIC, LMR Lo-Mendell Ruben
