Skip to main content

Table 4 Observed regressed on predicted utility using OLS and QR

From: The validation of published utility mapping algorithms: an example of EORTC QLQ-C30 and EQ-5D in non-small cell lung cancer

MappingOLSQR (10%)QR (25%)QR (50%)QR (75%)QR (90%)
InterceptCoefficient: predicted valueInterceptCoefficient: predicted valueInterceptCoefficient: predicted valueInterceptCoefficient: predicted valueInterceptCoefficient: predicted valueInterceptCoefficient: predicted value
Young et al. (2015) [12]0.0710.938−0.2701.209−0.0991.069−0.0221.0760.2140.8420.4440.619
Khan and Morris (2014) [13]−1.9142.915−1.9003.822−1.4383.241−1.1462.924−0.7242.384−0.3661.924
Khan et al. (2016) [14]−1.1534.009−2.8445.155−2.1634.266−2.0734.277−1.3513.295−0.6812.397
  1. Key: OLS Ordinary least squares, QR Quantile regression