Table 1.

Model Fit Statistics from the Longitudinal Latent Profile Analyses of Depressive Symptoms Across the First Six Waves.

	AIC	BIC	SABIC	LMR LRT p value	Entropy	Minimum Probabilities
1-Class	106765.66	106836.83	106798.70	N/A	N/A	N/A
2-Class	103393.39	103506.07	103445.70	< .001	0.76	0.91
3-Class	102740.69	102894.88	102812.27	.153	0.71	0.83
4-Class	102662.98	102858.69	102753.83	.052	0.72	0.80
5-Class	102362.23	102599.45	102472.36	.055	0.72	0.67

Note: AIC = Akaike Information Criterion; BIC = Bayesian Information Criterion; SABIC = Sample-Adjusted Bayesian Information Criterion. LMR LRT = Lo-Mendell-Rubin Likelihood Ratio Test. Lower AIC, BIC, and SABIC are considered fit. Significant LMR LRT indicates the k+1 model fits the data better than the k model. Entropy and probabilities closer to 1 are considered better quality of profile classification. Classification probabilities >= .70 are considered acceptable. There is no clear cut-off point for the value of entropy to ensure a minimum level of good classification but a value of 0.80 is considered high, 0.60 is considered medium, and 0.40 is considered low entropy.