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. 2020 Oct 25;12(11):3268. doi: 10.3390/nu12113268

Table 3.

Model fit information for LCPA models fit to data.

Class N. of Parameters AIC BIC Entropy VLMR a BLRT a
Daily dietary patterns
2 34 591,109.562 591,359.409 0.993 p < 0.001 p < 0.001
3 46 580,090.445 580,428.473 0.996 p < 0.001 p < 0.001
4 58 575,221.906 575,648.116 0.873 p < 0.001 p < 0.001
5 b 70 571,428.053 571,942.444 0.867 p < 0.001 p < 0.001
6 82 569,268.543 569,871.116 0.886 p = 0.8711 p < 0.001
Dinner dietary patterns
2 34 540,270.913 540,517.904 0.999 p < 0.001 p < 0.001
3 46 528,976.751 529,310.916 0.982 p < 0.001 p < 0.001
4 58 513,747.784 514,169.122 0.999 p < 0.001 p < 0.001
5 70 512,479.929 512,988.440 0.983 p = 0.0107 p < 0.001
6 c 82 501,781.884 502,377.569 0.976 p < 0.001 p < 0.001
7 94 498,611.403 499,294.262 0.971 p = 0.5023 p < 0.001

Note. AIC = Akaike information criterion; BIC = Bayesian information criterion; BLRT = bootstrapped likelihood ratio test; LCPA = latent class profile analysis; VLMR = Vuong–Lo–Mendell–Rubin likelihood ratio test. a Chi-square statistic for the VLMR and the BLRT; when non-significant (p > 0.05), the VLMR and the BLRT test provide evidence that the K-1 class model fits the data better than the K-class model. b The 5-class model was selected based on its having a smaller BIC than the 4-class model, and non-significant VLMR in the 6-class model. c The 6-class model was selected based on its having a smaller BIC than the 5-class model, and non-significant VLMR in the 7-class model.