Model

r-squared

F-ratio

Significance p-value

Variables selected

Coefficients

Std. error

t

Sig. p-value

95% CI

Multiple Regression

Male

Female

0.021

0.061

16

41

<0.001

<0.001

Male Model

Constant Pcalprot

Age

Race

Female Model

Constant Pcalprot

Race

Educat

Exerc

27

 0.093

-0.038

-0.46

23

0.079

1.6

-0.81

0.079

0.88

0.017

0.012

0.21

0.68

0.019

0.29

0.12

0.15

31

5.6

-3.1

-2.6

34.5

4.2

5.5

-7.0

-4.6

<0.001

<0.001

<0.05

<0.05

<0.001

<0.001

<0.001

<0.001

<0.001

(25.3-28.7)

(.060-.125)

(-.061- -.014)

(-.88- -.04)

(22.3- -25.0)

(.043-.12)

(1.0-2.2)

(-1.0- -.59)

(.41-1.0)

Multiple Regression with interaction terms

Male

Female

Male

Female

0.021

0.061

16

42

<0.001

<0.001

Male Model

Constant Pcalprot

Age

Race

Female Model

Constant Pcalprot

educat

RaceXEducat

Exerc

27

 0.093

-0.038

-0.46

26

0.081

-1.7

0.79

0.069

0.88

0.017

0.012

0.21

0.58

0.019

0.17

0.13

0.15

31

5.6

-3.1

-2.2

44

4.4

-10

6.0

4.5

<0.001

<0.001

<0.05

<0.05

<0.001

<0.001

<0.001

<0.001

<0.001

(25.3-28.7)

(.060-.125)

(-.061- -.014)

(-.88- -.04)

(24.6- -26.8)

(.045-.12)

(-2.1- -1.4)

(.53- 1.0)

(.39-.99)

Multiple Regression with interaction terms and inverse exponential transformation

Male

Female

0.020

0.053

15.7

28.1

<0.001

<0.001

Male Model

Constant RecipPcalprot

RecipAge

RecipRace

Female Model

Constant RecipPcalprot

RecipRace

Recip-

RaceXEducat

RecipExerc

RecipEducat

3.2

-0.91

5.0

0.44

3.6

-.66

-.29

.28

-.065

.151

.034

.17

1.8

.018

.049

.18

.058

.073

.018

.065

92

-5.5

2.9

2.5

73

-3.7

-5.8

3.8

-3.5

-2.3

<0.001

<0.001

<0.05

<0.05

<0.001

<0.001

<0.001

<0.001

<0.001

<0.05

(3.1-3.2)

(-1.2- -.58)

(1.6- 8.5)

(.010- .079)

(3.5- 3.7)

(-1.0- -.31)

(-.39- -.20)

(.14- .42)

(.10-.030)

(-.28- -.023)

Model

Hosmer

Lemeshow

Test

Chi square

Significance

p-value

G-squared

Log

Likelihood

Ratio

Variables selected

Coefficients

Std. error

Wald

Sig. p-value

Logistic

Regression

Male

Female

4.4

6.1

.82

.64

1729

2659

Male

Model

Constant

Pcalprot

Age

Educat

Exerec

Female

Model

Constant

Pcalprot

Educat

Exerec

Race

-0.789

  0.046

-0.029

-0.215

  0.181

- 2.23

  0.029

-0.337

  0.350

  0.431

1.3

.011

.009

.065

.086

.31

.008

.053

.075

.012

1.2

17

10

11

4.5

52

12

40

22

13

.26

<.001

<.01

<.01

<.05

<.001

<.001

<.001

<.001

<.001

Logistic Regression

with

interaction terms

Male

Female

4.4

7.0

.82

.53

1729

2655

Male

Model

Constant

Pcalprot

Age

Educat

Exerec

Female

Model

Constant

Pcalprot

Educat

Exerec

RaceXEducat

-0.789

  0.046

-0.029

-0.215

  0.181

-1.7

0.030

-.61

0.34

0.22

.694

.011

.009

.065

.086

.271

.008

.075

.075

.053

1.3

17

10

11

4.5

39

13

66

21

17

.26

<.001

<.01

<.01

<.05

<.001

<.001

<.001

<.001

<.001

Logistic Regression

With

Interaction terms

and inverse exponential

transformation

Execution not possible