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Table 2 Goodness-of-fit results from full sample

From: From KIDSCREEN-10 to CHU9D: creating a unique mapping algorithm for application in economic evaluation

Model specification (1) (2) (3) (4) (5) (6) (7)
  Mean CHU9D Min CHU9D Max CHU9D MAE RMSE MAE RMSE
Observed 0.8082 0.3479 1.0000
Method 1: Ordinary least squares estimator
  Model 1 0.8082 0.4535 0.9817 0.0978 0.1238
  Model 2 0.8082 0.4909 1.0342 0.0950** 0.1193* 0.0946 0.1190
Method 2: Censored least absolute deviations estimator
  Model 1 0.8185 0.4473 0.9944 0.0971 0.1243
  Model 2 0.8179 0.4281 1.0802 0.0971 0.1247 0.0944 0.1219
Method 3: MM-estimator       
  Model 1 0.8136 0.4156 1.0019 0.0972 0.1243 0.0971 0.1243
  Model 2 0.8146 0.4807 1.0555 0.0946* 0.1199** 0.0937 0.1193
Method 4: Generalised linear model
  Model 1 0.8082 0.4693 0.9950 0.0975 0.1240
  Model 2 0.8082 0.3760 0.9483 0.0971 0.1217
  1. CHU9D – Child Health Utility 9D; MAE – mean absolute error; RMSE – root mean squared error.
  2. *denotes the smallest value in the column; **denotes the second smallest value in the column.
  3. The adjusted goodness-of-fit results by specifying the maximum predicted utility score to be 1.
  4. The R-square statistics for Model 1 and 2 are 0.36 and 0.41, respectively.