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Table 1 Performance of latent class growth model and growth mixture model

From: Interpretable classifiers for prediction of disability trajectories using a nationwide longitudinal database

  BIC    
LGCM
 linear 105,530.680    
 quadratic 105,345.372    
 cubic 105,359.053    
LCGM BIC Entropy VLMR-LRT Smallest class
 1-class 111,004.715    100%
 2-class 105,054.609 0.942 0.0000 16.173%
 3-class 102,817.976 0.892 0.0000 8.093%
 4-class 101,585.221 0.904 0.0018 3.720%
 5-class 100,586.689 0.881 0.0009 4.278%
 6-class 99,933.216 0.862 0.0153 3.068%
GMM
 3-class 102,109.346 0.929 0.0000 7.158%
  1. Abbreviations: BIC Bayesian information criteria, VLMR-LRT VUONG-LO-MENDELL-RUBIN likelihood ratio test, LGCM Latent growth curve model, LCGM Latent class growth model, GMM, growth mixture model