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Table 3 Parameter estimates and fit statistics of aggregate level models using OLS and WLS regression

From: Rural population’s preferences matter: a value set for the EQ-5D-3L health states for China’s rural population

Variable Main effects N3 D1
OLS WLS OLS WLS OLS WLS
Coef SE Coef SE Coef SE Coef SE Coef SE Coef SE
Constant 0.071 0.007 0.071 0.007 0.067 0.007 0.070 0.007     
MO2 0.102 0.005 0.100 0.005 0.101 0.005 0.099 0.005 0.167 0.007 0.166 0.007
MO3 0.279 0.007 0.280 0.007 0.275 0.007 0.279 0.007 0.365 0.014 0.370 0.014
SC2 0.102 0.005 0.101 0.005 0.103 0.005 0.101 0.005 0.169 0.007 0.169 0.007
SC3 0.242 0.006 0.244 0.006 0.239 0.007 0.243 0.007 0.330 0.015 0.336 0.015
UA2 0.087 0.006 0.085 0.006 0.086 0.006 0.084 0.006 0.151 0.007 0.150 0.007
UA3 0.222 0.006 0.223 0.006 0.217 0.007 0.222 0.007 0.308 0.013 0.313 0.014
PD2 0.110 0.006 0.110 0.006 0.110 0.006 0.109 0.006 0.175 0.007 0.175 0.007
PD3 0.237 0.006 0.240 0.006 0.232 0.007 0.239 0.007 0.323 0.014 0.329 0.014
AD2 0.075 0.005 0.074 0.005 0.074 0.005 0.073 0.005 0.139 0.009 0.138 0.009
AD3 0.177 0.006 0.180 0.006 0.172 0.007 0.178 0.007 0.262 0.014 0.267 0.014
N3      0.016 0.009 0.005§ 0.009     
D1          − 0.073 0.013 − 0.077 0.014
I2          0.009§ 0.017 0.015§ 0.018
I2sq          − 0.000§ 0.003 − 0.000§ 0.003
I3          − 0.022 0.013 − 0.028 0.013
I3sq          0.001§ 0.003 0.003§ 0.002
Fit statistics             
 Adjusted R2 0.993 0.995 0.993 0.995 0.999 0.999
 MAE 0.018 0.017 0.017 0.017 0.017 0.017
 RMSE 0.024 0.024 0.024 0.024 0.024 0.023
 No. (of 97) > 0.025 28 29 27 28 27 28
 No. (of 97) > 0.05 2 3 2 3 2 2
  1. P < 0.01 and Heteroskedasticity-robust standard error for all regression coefficients unless otherwise stated; there are no health states that had an MAE greater than 0.1 for all models; OLS, ordinary least square; WLS, weighted least square; Coef, coefficient; SE, standard error; MAE, mean absolute error; RMSE, root mean squared error; 0.01 ≤ P ≤ 0.05; 0.05 < P ≤ 0.1; §P > 0.1