What do Australian adults eat for breakfast? A latent variable mixture modelling approach for understanding combinations of foods at eating occasions

Table 1 Model fit indices for latent profiles of food combinations at breakfast eating occasions^a

	2 classes	3 classes	4 classes	5 classes	6 classes
Men
Loglikelihood	−60,711.023	−59,309.719	−58,281.212	−57,825.658	− 57,424.792
Entropy	0.819	0.873	0.872	0.868	0.849
BIC	122,871.330	120,642.489	119,181.015	118,854.561	118,637.483
adjusted BIC	122,312.086	119,857.641	118,170.563	117,618.505	117,175.822
^bLMR-LRT	5586.967, P < 0.001	2808.885, P < 0.001	2042.776, P < 0.001	912.682, P = 0.01	794.951, P = 0.08
Women
Loglikelihood	−67,230.626	−65,773.386	−64,449.367	−63,598.615	−63,454.789
Entropy	0.863	0.881	0.878	0.926	0.889
BIC	135,936.216	133,617.594	131,564.811	130,458.564	130,766.168
adjusted BIC	135,376.959	132,832.727	130,554.335	129,222.479	129,304.474
^bLMR-LRT	6122.822, P = 0.12	2900.629, P < 0.0001	2643.024, P < 0.0001	1742.887, P < 0.0001	336.794, P = 0.13

^aAIC Akaike Information Criterion, BIC Bayesian Information Criterion, BS Bootstrap, LMR Lo-Mendell-Rubin, LRT likelihood ratio test
^bAdjusted Lo-Mendell-Rubin likelihood ratio test for k versus k-1 profiles. Values are two times the loglikelihood difference and corresponding p-value

ISSN: 1479-5868