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Table 2 Indices of model fit from latent class growth analyses of chronic pain in arthritis and cancer

From: General and disease-specific pain trajectories as predictors of social and political outcomes in arthritis and cancer

k AIC BIC Entropy VLMR-LRT p
Whole sample
 1 177,684.561 177,839.979
 2 133,343.915 133,476.949 0.871 < 0.001
 3 130,255.155 130,454.705 0.848 < 0.001
 4 126,764.571 127,030.638 0.851 < 0.001
 + Quadratic 124,206.071 124,501.701 0.859  
 + Cubic 123,577.681 123,902.874 0.869  
 5 125,988.308 126,320.892 0.901 < 0.001
Arthritis
 1 14,198.301 14,298.893
 2 11,316.565 11,407.577 0.702 < 0.001
 3 11,200.776 11,339.689 0.702 0.008
 4 11,105.289 11,292.103 0.757 0.001
 + Quadratic 10,942.055 11,148.029 0.841  
 + Cubic 10,914.137 11,139.272 0.850  
 5 11,084.221 11,318.936 0.778 0.29
Cancer
 1 6298.329 6384.856
 2 4662.729 4736.895 0.904 < 0.001
 3 4474.875 4586.123 0.998 0.052
 + Quadratic 4420.884 4544.492 0.998  
 + Cubic 4390.708 4526.677 0.998  
 4 4198.800 4347.131 0.998 0.37
 5 4128.545 4313.958 0.947 0.37
  1. In the whole sample and cancer subsample, the five class linear models failed to converge
  2. AIC Akaike information criterion, BIC Bayesian information criterion, VLMR-LRT Vuong-Lo-Mendell-Rubin likelihood ratio test
  3. Statistics highlighted in bold are the best fitting for a particular index
  4. Standard deviations are reported in brackets for continuous variables (BMI, age, GHQ-12 and social engagement measures)