Skip to main content

Table 6 Marginal model and random-effects models analysing time-fixed and time varying covariates

From: Choosing marginal or random-effects models for longitudinal binary responses: application to self-reported disability among older persons

  Marginal model* GEE Random model* likelihood integration
  Estimate SE p value Estimate SE p value
Baseline       
Living alone -0.31 0.09 0.0004 -0.66 0.18 0.0002
BMI (kg/m2)       
   < 25 (ref) 0    0   
   25 – 29 0.30 0.10 0.002 0.69 0.20 0.0005
   ≥ 29 0.75 0.12 < 0.0001 1.46 0.23 < 0.0001
Visual acuity       
   ≤ 2/10 0.64 0.20 0.001 1.21 0.35 0.0006
   > 2/10 (ref) 0    0   
Perceived health       
   Bad or very bad 0.76 0.15 < 0.0001 1.43 0.28 < 0.0001
Follow-up       
Hospitalised (past year) 0.26 0.05 < 0.0001 0.49 0.11 < 0.0001
Temporarily bed confined (past year) 0.39 0.07 < 0.0001 0.73 0.15 < 0.0001
Number of falls ≥ 2 (past year) 0.23 0.08 0.004 0.49 0.15 0.0013
  1. *adjusted on time since inclusion, age at inclusion, age × time, baseline disability and death