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Table 4 Predictive performance of direct and indirect mapping models for the EQ‑5D‑5L (N = 238)

From: Developing mapping algorithms to predict EQ-5D health utility values from Bath Ankylosing Spondylitis Disease Activity Index and Bath Ankylosing Spondylitis Functional Index among patients with Ankylosing Spondylitis

Model type

Mean

SD

Min

Max

MAE

RMSE

Spearman

CCC

Average rank

EQ-5D-5L value

0.7388

0.2694

-0.3480

1.0000

     

Full sample

        

 OLS

0.7388

0.2220

0.1635

1.0253

     

 CLAD

0.8042

0.1808

0.3349

1.0419

     

 Tobit

0.7716

0.2568

0.1083

1.1165

     

 ALDVMM

0.7450

0.2081

0.1617

0.9805

     

 BM

0.7575

0.2003

0.1513

0.9611

     

 Ologit

0.7561

0.2235

-0.0254

0.9745

     

 Mlogit

0.7573

0.2149

0.0200

0.9788

     

Cross validation

        

 OLS

0.7396

0.2230

0.1472

1.0286

0.1091

0.1567

0.8471

0.7990

3

 CLAD

0.7729

0.2581

0.0865

1.1269

0.1225

0.1666

0.8550

0.8020

6

 Tobit

0.7928

0.2270

0.1099

1.1310

0.1182

0.1759

0.8491

0.7560

7

 ALDVMM

0.7457

0.2078

0.1484

0.9835

0.1044

0.1567

0.8523

0.7880

2

 BM

0.7312

0.2300

-0.0171

0.9791

0.1027

0.1533

0.8570

0.8130

1

 Ologit

0.7567

0.2250

-0.0874

0.9773

0.1012

0.1588

0.8551

0.7960

5

 Mlogit

0.7569

0.2172

0.0069

0.9830

0.1006

0.1578

0.8485

0.7930

4

  1. CLAD censored least absolute deviations, ALDVMM adjusted limited dependent variable mixture model, BM beta-mixture model, Ologit ordered logit, Mlogit multinomial logit. Bold indicates the best model in this performance indicator