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Table 5 Parameter estimates for population-average model using robust regression with pweights

From: Is the value of a life or life-year saved context specific? Further evidence from a discrete choice experiment

Predictor β SE z Sig. β SE z Sig.
  Lives saved Life-years saved
Medical(B – A)     ns     ns
Cure(B – A) -0.8476 0.110 -7.68 0.000 -0.8330 0.105 -7.93 0.000
AgeGrp_(B – A)    χ2 = 130 0.000    χ2 = 28.9 0.000
AgeGrp1(B – A) 1.2894 0.148 8.72 0.000 0.7448 0.144 5.17 0.000
AgeGrp2(B – A) 0.5936 0.138 4.30 0.000 0.3001 0.132 2.28 0.023
AgeGrp4(B – A) -0.3810 0.110 -3.45 0.001 0.0187 0.130 0.14 0.886
Evidence(B – A) 0.6857 0.093 7.34 0.000 0.6572 0.093 7.05 0.000
Fault(B – A) -0.5822 0.097 -5.98 0.000 -0.6560 0.104 -6.31 0.000
$Private(B – A)^ -0.0055 0.002 -2.49 0.013 -0.0077 0.002 -3.59 0.000
Effect(B – A) 0.0338 0.004 8.43 0.000 0.0006 0.000 7.53 0.000
$Cost(B – A)^ -0.0060 0.001 -4.50 0.000 -0.0057 0.001 -4.22 0.000
HlthCard*Q -0.0456 0.018 -2.52 0.012 -0.0454 0.018 -2.51 0.012
SIEFA_Econ*Q/1000 0.0693 0.022 3.15 0.002 0.0794 0.022 3.58 0.000
(Constant) -0.3415 0.118 -2.89 0.004 -0.3995 0.117 -3.43 0.001
     N = 2329     N = 2329
     Wald χ2 = 352.32, df = 11, p = 0.000     Wald χ2 = 346.91, df = 11, p = 0.000
     Log-likelihood = -1234.69, Pseudo R2 = 0.2350     Log-likelihood = -1239.33, Pseudo R2 = 0.2321
  1. ^Dollar values expressed in AUD100,000s.
  2. Reference category is 'working-age adults'. First, second and fourth dummies denote 'young children', 'young adults' and 'older-age retirees', respectively. Joint significance of dummies evaluated using Wald statistic on chi-square distribution.
  3. Effect(B – A) gives the incremental effectiveness of profile B compared to profile A defined in terms of terms of lives saved for the 'lives-saved' model and life-years saved for the 'life-years saved' model.