Table 2.
Model Fit Statistics for Gray Matter and White Matter Latent Profile Analyses.
| Classes | Class Proportions | Loglikelihood | AIC | BIC | SABIC | BLRT | p BLRT | LMR | p LMR | Entropy |
|---|---|---|---|---|---|---|---|---|---|---|
| GM Model (n = 156) | ||||||||||
| 2 | 0.56 / 0.44 | −8539.163 | 17188.33 | 17356.07 | 17181.98 | 619.91 | p<.001 | 613.52 | .002 | .933 |
| 3 | 0.33 / 0.49 / 0.19 | −8435.054 | 17018.11 | 17243.80 | 17009.56 | 208.22 | p<.001 | 206.07 | .337 | .933 |
| a4 | 0.21 / 0.38 / 0.22 / 0.19 | −8340.402 | 16866.80 | 17150.44 | 16856.07 | 189.30 | p<.001 | 187.35 | .194 | .947 |
| 5 | Model not well-identified | |||||||||
| WM Model (n = 144) | ||||||||||
| 2 | 0.54 / 0.46 | −8419.603 | 16961.21 | 17142.37 | 16949.35 | 548.95 | p<.001 | 543.74 | .003 | .922 |
| 3 | 0.51 / 0.33 / 0.15 | −8316.315 | 16796.63 | 17040.16 | 16780.69 | 206.58 | p<.001 | 204.62 | .178 | .933 |
| a4 | 0.19 / 0.19 / 0.24 / 0.38 | −8231.739 | 16669.48 | 16975.37 | 16649.45 | 169.15 | p<.001 | 167.55 | .417 | .939 |
| 5 | 0.16 / 0.23 / 0.33 / 0.15 / 0.13 | −8168.981 | 16585.96 | 16954.22 | 16561.85 | 125.51 | p<.001 | 124.32 | .348 | .956 |
| 6 | Model not replicated | |||||||||
Note: GM = Gray matter; WM = White matter; AIC = Akaike Information Criterion; BIC = Bayesian Information Criterion; SABIC = sample-size adjusted BIC; BLRT = Bootstrapped Likelihood Ratio Test; LMR = Lo-Mendell-Rubin Likelihood.
Lower values of AIC, BIC, SABIC demonstrate better model fit. pBLRT < .05 indicates that the k-class model is a better fit to the data than the k-1 class model. pLMR small p-values indicate that the k-class model fits better to data than the k-1 class model. Entropy value close to 1 indicates excellent classification of subjects into latent classes.
Denotes the selected models. Although the 5-class WM model (under WM model) is the best fit model regarding the fit indices, it does not demonstrate the appropriate separation of the classes compared to 4-class model.