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Table 3 Goodness of fit results from validation analysis

From: Mapping the Minnesota living with heart failure questionnaire (MLHFQ) to EQ-5D-5L in patients with heart failure

 

Validation method (3-fold)

Pooled sample (N = 141)

Mean utility

RMSE

MAE

Ab

diff < 0.03

Ab

diff < 0.05

Observed

0.6619

    

Model 1

 OLS

0.6624

0.2220

0.1783

9.9

16.2

 GLM

0.6153

0.2220

0.1916

3.5

9.2

 CLAD

0.6925

0.2240

0.1730

12.7

19.7

 MFP

0.7164

0.2288

0.1713

12.7

18.3

 MM

0.7254

0.2309

0.1717

12.0

20.4

 BETA

0.7246

0.2378

0.1775

10.6

16.2

Model 2

 OLS

0.6696

0.2187

0.1738

8.5

16.2

 GLM

0.6711

0.2197

0.1740

9.2

15.5

 CLAD

0.7304

0.2316

0.1710

7.0

21.8

 MFP

0.7224

0.2268

0.1684

11.3

16.9

 MM

0.7313

0.2292

0.1688

11.3

16.9

 BETA

0.7286

0.2355

0.1761

4.9

12.0

Model 3

 OLS

0.6671

0.2153

0.1711

12.0

17.6

 GLM

0.6671

0.2153

0.1711

12.0

17.6

 CLAD

0.7173

0.2268

0.1700

11.3

14.8

 MFP

0.7086

0.2204

0.1676

13.4

20.4

 MM

0.7177

0.2229

0.1689

9.2

16.9

 BETA

0.7347

0.2318

0.1740

11.3

16.9

Indirect mapping

 OLOGIT

0.6498

0.2353

0.1935

8.5

12.7

  1. Dependant variable: EQ-5D-5 L utility score; Independent variables: Model 1 - MLHF total score; Model 2 – MLHF domain scores; Model 3 – MLHF item scores (Item 04, 17 and 21).
  2. Abs diff. < 0.03 (0.05)% - proportion of predicted utilities whose absolute values deviate from the mean of the observed utility values by less than 0.03 (0.05); RMSE – Root Mean Square Error; MAE – Mean Absolute Error.
  3. OLS - Ordinary least square; GLM - Generalized linear modelling; CLAD - Censored least absolute deviations; MFP - Multivariable fractional polynomials; MM - Robust MM estimator; BETA - Mixture beta regression model; OLOGIT ordered logit (indirect response mapping).