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Table 3 Model fit statistics for latent class analysis at baseline, T1, T2

From: Health status transitions in community-living elderly with complex care needs: a latent class approach

  T0 T1 T2
  2 classes 3 classes 4 classes 5 classes 4 classes 5 classes 4 classes 5 classes
Sequential model comparisons 2 vs. 1 classes 3 vs. 2 classes 4 vs. 3 classes 5 vs. 4 classes 4 vs. 3 classes 5 vs. 4 classes 4 vs. 3 classes 5 vs. 4 classes
LMR LRT         
Log-likelihood value (c+1 classes) 13265.31 13595.67 12239.68 12093.26 8366.61 8119.41 4603.94 4449.05
-2 difference in log likelihood 1468.19 2711.98 292.85 107.55 494.40 108.374 309.774 77.03
p value 0.000 0.000 0.0006 0.307 0.000 0.286 0.000 0.198
Adjusted LMR LRT 1458.80 2375.46 290.97 106.86 490.03 107.64 265.99 76.43
p value 0.000 0.000 0.0006 0.309 0.000 0.289 0.000 0.198
Information criterion         
AIC 25148.43 24483.26 24192.52 24296.97 16244.82 16348.45 9072.11 9039.11
BIC 25365.96 24493.48 24207.69 24848.37 16258.87 16858.66 9426.66 9483.32
Adjusted BIC 25229.38 24487.13 24198.16 24502.15 16249.34 16512.53 9150.57 9137.40
Entropy 0.814 0.791 0.805 0.765 0.815 0.804 0.830 0.849
Condition number 0.0029 0.309 0.233 0.0012 0.0524 0.0014 0.0301 0.022
  1. LMR-LRT = Lo-Mendell-Rubin Likelihood Ratio Test; AIC: Akaike Information Criterion; BIC: Bayesian Information Criterion.
  2. Condition number = ratio of largest Eigen value to the smallest Eigen value for the Fisher information matrix. Values less than 10E-09 indicate problem with model identification.