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. Author manuscript; available in PMC: 2011 Nov 1.
Published in final edited form as: Dev Psychol. 2010 Nov;46(6):1543–1555. doi: 10.1037/a0020549

Table 3.

Relative Model Fit by Number of Latent Classes of ADHD Trajectories

Classes Log-Likelihood Number of Parameters Entropy AIC BIC Adj. BIC VLMR
1 −3056 30 n/a 6171 6307 6212 n/a
2 −3002 45 .712 6093 6298 6155 108, p = .94
3 −2887 60 .745 5893 6166 6166 166, p < .001

Note. For entropy, higher numbers (up to 1.0) indicated greater certainty of classification. For AIC, BIC, and sample-size adjusted BIC, lower values indicate better fit, considering parsimony. Vuong-Lo-Mendell-Rubin (VLMR) tests that k classes are needed for better fit, vs. k-l classes being adequate.