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Table 7 Real data results: parameter estimates with standard errors and p-values from the two-latent classes model with covariates

From: Joint latent class model: Simulation study of model properties and application to amyotrophic lateral sclerosis disease

number of observations 2525
number of patients 497
average number of longitudinal measure 5
number of events 129
censoring rate 0.74
Sub-model Parameter Estimate (se) p-value
Multinomial logistic regression ξ01 2.22 (0.31) <0.001
Weibull model ζ11 0.48 (0.17) 0.004
  ζ21 1.48 (0.08) <0.001
  ζ12 0.68 (0.21) 0.001
  ζ22 1.64 (0.12) <0.001
  𝜗1 -0.05 (0.01) 0.008
  𝜗2 -0.05 (0.03) 0.079
  𝜗3 -0.03 (0.01) <0.001
  𝜗4 -0.41 (0.12) <0.001
  𝜗5 0.04 (0.01) <0.001
Linear mixed model : fixed effects \(\hat {\beta }_{01}\) 9.79 (4.02) 0.015
  β11 -2.32 (0.27) <0.001
  β02 7.83 (4.12) 0.057
  β12 -4.06 (0.39) <0.001
  γ1 (SO) -0.06 (0.02) <0.001
  γ2 (BMI) -0.13 (0.05) 0.009
  γ3 (MUSC) 0.16 (0.00) <0.001
  γ4 (SVC) 1.04 (0.18) <0.001
  γ5 (MCV) 0.10 (0.04) 0.007 1
  γ6 (SO ×tj) 0.02 (0.00) <0.001
  γ7 (MUSC ×tj) 0.01 (0.00) <0.001
  γ8 (SVC ×tj) 0.06 (0.02) 0.018
Linear mixed model : random effects \(\sigma ^{2}_{b_{0}}\) 14.10 (0.00)  
  \(\sigma ^{2}_{b1}\) 0.18  
  \(\sigma ^{2}_{\epsilon,1}\) 1.97  
  1. Note: the following covariates and their interactions with time (if significant) are presented: SO (Symptom Onset), BMI (Body Mass Index), MUSC (Muscular capacity), SVC (Slow vital capacity), MCV (Mean corposcular volume)