Table 6 Model performance of three regression methods for mapping the PHQ-8 to the SF-6D utility scores

1

BETAMIX M1a

1 component without truncation

Probability mass at full health

0.0008

0.0587

0.0746

10

9

9.2

2

BETAMIX M1b

2 components without truncation

Probability mass at full health

0.0060

0.0575

0.0749

9

10

9.2

3

BETAMIX M1c

2 components with truncation

Probability mass at full health

N/A

N/A

N/A

N/A

N/A

N/A

4

BETAMIX M1d

2 components with truncation

Probability mass at full health and truncation point

N/A

N/A

N/A

N/A

N/A

N/A

5

BETAMIX M2a

1 component without truncation

Probability mass at full health

0.0013

0.0539

0.0695

6

6

6

6

BETAMIX M2b

2 components without truncation

Probability mass at full health

0.0055

0.0527

0.0693

2

5

3.5

7

BETAMIX M2c

2 components with truncation

Probability mass at full health

N/A

N/A

N/A

N/A

N/A

N/A

8

BETAMIX M2d

2 components with truncation

Probability mass at full health and truncation point

N/A

N/A

N/A

N/A

N/A

N/A

9

BETAMIX M3a

1 component without truncation

Probability mass at full health

0.0020

0.0533

0.0683

5

2

3.5

10

BETAMIX M3b

2 components without truncation

Probability mass at full health

0.0057

0.0519

0.0683

1

1

1

11

BETAMIX M3c

2 components with truncation

Probability mass at full health

N/A

N/A

N/A

N/A

N/A

N/A

12

BETAMIX M3d

2 components with truncation

Probability mass at full health and truncation point

N/A

N/A

N/A

N/A

N/A

N/A

13

OLS M1

0.0000

0.0587

0.0754

11

11

11

14

OLS M2

0.0000

0.0545

0.0710

7

7

7

15

OLS M3

0.0000

0.0532

0.0686

3

3

3

16

TOBIT M1

0.0000

0.0587

0.0754

12

12

12

17

TOBIT M2

0.0000

0.0545

0.0710

8

8

8

18

TOBIT M3

0.0000

0.0532

0.0686

4

4

4