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Table 2 Model assessment with maximum likelihood with robust standard errors (MLR)

From: Decomposing the heterogeneity of depression at the person-, symptom-, and time-level: latent variable models versus multimode principal component analysis

Analysis type   Degrees of freedom AIC BIC
EFA (n = 147) 1-factor 36 3093 3201
2-factor 47 3090 3230
3-factor 57 3082 3252
LCM (n = 147) 1-class 24 3460 3532
2-class 49 3161 3307
3-class 74 3097 3318
4-class 99 3071 3366
5-classa 124 3052 3422
LCGM (n = 82) 1-class 12 4670 4699
2-class 16 4363 4401
3-class 20 4267 4315
4-class 24 4220 4278
5-classa 28 4173 4240
GMM (n = 82) 1-class 15 4188 4224
2-class 21 4163 4213
3-class 27b 4146 4210
4-class 33b 4158 4237
  1. FA factor analysis, LCM latent class models, LCGM latent class growth models, GMM growth mixture models
  2. asmallest class contains < 10 subjects
  3. bsmallest class contains < 5 subjects