BMC Medical Research Methodology

Table 1 Likelihood statistics for GMM models of change with four time points

From: Growth mixture models: a case example of the longitudinal analysis of patient‐reported outcomes data captured by a clinical registry

	-2LL	df	AIC	BIC	SABIC
LCGA
Intercept-only	-46,156.95	6	92,325.90	92,367.36	92,348.32
Linear	-46,065.15	9	92,148.29	92,210.52	92,181.92
Quadratic	-45,910.73	13	91,847.46	91,937.35	91,896.04
GMM – quadratic
1-class	-45,910.73	13	91,846.46	91,937.35	91,896.04
2-class	-45,910.73	27	91,875.47	92,062.16	91,976.36

Note. LCGA Latent class growth analysis, GMM Growth mixture model, LL Log-likelihood, df degrees of freedom, AIC Akaike’s information criterion, BIC Bayesian information criterion, SABIC Sample size adjusted BIC

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ISSN: 1471-2288

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