Table 8 Regression algorithms for converting Barthel data to AQoL scores

0.1817

0.0393

4.63

0.000

-0.0180

0.0070

-2.56

0.011

0.0020

0.0003

6.38

0.000

0.6536

F_652,597 = 2.66

0.000

Obs = 1252

Ids = 653

F_2,597 = 80.00

0.000

R² _within = 0.211

R² _between = 0.689

R² _overall = 0.631

0.2068

0.0471

4.39

0.000

-0.0201

0.0081

-2.47

0.014

0.0020

0.0003

4.39

0.000

0.6579

F_597,528 = 2.75

0.000

Obs = 1128

Ids = 598

F_2,528 = 67.43

0.000

R² _within = 0.203

R² _between = 0.639

R² _overall = 0.581

0.0071

0.0089

0.80

0.425

-0.0053

0.0067

-0.80

0.429

0.0017

0.0004

3.81

0.000

-

-

-

ns

Obs = 120

Ids = 96

F_2,95 = 51.27

0.000

R² _overall = 0.574

0.1160

0.0335

3.47

0.001

0.0450

0.0192

2.35

0.019

0.0631

0.0168

3.76

0.000

0.1173

0.0280

4.18

0.000

0.0520

0.0119

4.35

0.000

0.0249

0.0135

1.85

0.065

0.6467

F_652,594 = 2.54

0.000

Obs = 1252

Ids = 653

F_5,594 = 30.48

0.000

R² _within = 0.204

R² _between = 0.693

R² _overall = 0.631

0.1273

0.0411

3.10

0.002

0.0460

0.0230

2.00

0.046

0.0620

0.0184

3.36

0.001

0.1087

0.0302

3.60

0.000

0.0531

0.0128

4.15

0.000

0.0291

0.0151

1.93

0.054

0.6534

F_597,525 = 2.66

0.000

Obs = 1128

Ids = 598

F_5,525 = 25.64

0.000

R² _within = 0.196

R² _between = 0.644

R² _overall = 0.579

-0.0114

0.0103

-1.11

0.269

0.0341

0.0124

2.74

0.007

0.3176

0.0612

5.19

0.000

0.0368

0.0150

2.45

0.016

0.0553

0.0278

1.99

0.049

-

-

-

ns

Obs = 120

Ids = 96

F_4,95 = 38.02

0.000

R² _overall = 0.639