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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

Mapping

OLS

QR (10%)

QR (25%)

QR (50%)

QR (75%)

QR (90%)

Intercept

Coefficient: predicted value

Intercept

Coefficient: predicted value

Intercept

Coefficient: predicted value

Intercept

Coefficient: predicted value

Intercept

Coefficient: predicted value

Intercept

Coefficient: predicted value

Young et al. (2015) [12]

0.071

0.938

−0.270

1.209

−0.099

1.069

−0.022

1.076

0.214

0.842

0.444

0.619

Khan and Morris (2014) [13]

−1.914

2.915

−1.900

3.822

−1.438

3.241

−1.146

2.924

−0.724

2.384

−0.366

1.924

Khan et al. (2016) [14]

−1.153

4.009

−2.844

5.155

−2.163

4.266

−2.073

4.277

−1.351

3.295

−0.681

2.397

  1. Key: OLS Ordinary least squares, QR Quantile regression