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. 2017 Aug 16;37(33):7994–8002. doi: 10.1523/JNEUROSCI.1175-17.2017

Table 2.

LCMM model statistics

Between-model comparison
Log likelihood NPMa BIC Class 1b Class 2b Class 3b Class 4b
2 Classes −185.89 12 424.22 40.5% 59.5%
3 Classes −169.81 17 413.89 26.6% 12.7% 60.7%
4 Classes −159.67 22 415.47 7.6% 26.6% 11.4% 54.4%
Within the three-class model: fixed effects allowing for cubic time (t) trends
n (%) Coefficient SE Wald p
Class 1 21 (26) t 8.47 3.06 2.78 0.0055
t2 32.88 5.51 5.97 <0.0001
t3 0.13 1.84 0.07 0.9441
Class 2 10 (13) t −40.52 3.46 −11.69 <0.0001
t2 −34.27 3.95 −8.67 <0.0001
t3 −12.14 1.62 −7.51 <0.0001
Class 3 48 (61) t 4.29 2.52 1.71 0.0878
t2 −17.07 4.02 −4.25 0.0002
t3 −3.97 1.36 −2.92 0.0035
Within the three-class model: mean of posterior probabilities (%) in each class
Class 1 Class 2 Class 3
Class 1 (n = 21) 91 4 5
Class 2 (n = 10) 8 85 7
Class 3 (n = 48) 4 1 95

aNumber of model parameters.

bPosterior proportion for each class.