partial corr matrix = in ( * ) / variables = exercise …correlations control variables stress...

comment recursive path model of illness, figure 7.5, table 4.2. comment model diagram with ols estimates in figure 11.1.

comment observed means are 40.90 0.0 67.10 4.80 716.70.

comment but this model has no mean structure.

matrix data variables = exercise hardiness fitness stress illness/contents=mea

n sd n corr

/format=lower nodiagonal.

begin data

0 0 0 0 0

66.50 38.00 18.40 33.50 62.48

373 373 373 373 373

-.03

.39 .07

-.05 -.23 -.13

-.08 -.16 -.29 .34

end data.

comment vanishing partial correlations for conditional independences of a basi

s set.

partial corr matrix=in(*)/variables = exercise with stress by hardiness (1).

Partial Corr

Notes

Output Created

Comments

Input Filter

Weight

Split File

N of Rows in Working Data File

Matrix Input

Missing Value Handling Definition of Missing

Cases Used

Syntax

Resources Processor Time

Elapsed Time

03-JAN-2015 21:07:12

<none>

<none>

<none>

8

working data file

User defined missing values are treated as missing.Statistics are based on cases with no missing data for any variable listed.partial corr matrix=in(*)/variables = exercise with stress by hardiness (1).

00:00:00.02

00:00:00.00

Correlations

Control Variables stress

hardiness exercise Correlation

Significance (2-tailed)

df

-.058

.260

370

partial corr matrix=in(*)/variables = exercise with illness by fitness, stress

(2).

Partial Corr

Notes

Output Created

Comments

Input Filter

Weight

Split File


Matrix Input


Cases Used

Syntax


Elapsed Time

03-JAN-2015 21:07:12

<none>

<none>

<none>

8

working data file

User defined missing values are treated as missing.Statistics are based on cases with no missing data for any variable listed.partial corr matrix=in(*)/variables = exercise with illness by fitness, stress (2).

00:00:00.00

00:00:00.00

Correlations

Control Variables illness

fitness & stress exercise Correlation


df

.039

.450

369

partial corr matrix=in(*)/variables = hardiness with fitness by exercise (1).

Partial Corr

Notes

Output Created

Comments

Input Filter

Weight

Split File


Matrix Input


Cases Used

Syntax


Elapsed Time

03-JAN-2015 21:07:12

<none>

<none>

<none>

8

working data file

User defined missing values are treated as missing.Statistics are based on cases with no missing data for any variable listed.partial corr matrix=in(*)/variables = hardiness with fitness by exercise (1).

00:00:00.00

00:00:00.00

Correlations

Control Variables fitness

exercise hardiness Correlation


df

.089

.087

370

partial corr matrix=in(*)/variables = hardiness with illness by fitness, stres

s (2).

Partial Corr

Notes

Output Created

Comments

Input Filter

Weight

Split File


Matrix Input


Cases Used

Syntax


Elapsed Time

03-JAN-2015 21:07:12

<none>

<none>

<none>

8

working data file

User defined missing values are treated as missing.Statistics are based on cases with no missing data for any variable listed.partial corr matrix=in(*)/variables = hardiness with illness by fitness, stress (2).

00:00:00.00

00:00:00.00

Correlations

Control Variables illness

fitness & stress hardiness Correlation


df

-.081

.118

369

partial corr matrix=in(*)/variables = fitness with stress by exercise, hardine

ss (2).

Partial Corr

Notes

Output Created

Comments

Input Filter

Weight

Split File


Matrix Input


Cases Used

Syntax


Elapsed Time

03-JAN-2015 21:07:12

<none>

<none>

<none>

8

working data file

User defined missing values are treated as missing.Statistics are based on cases with no missing data for any variable listed.partial corr matrix=in(*)/variables = fitness with stress by exercise, hardiness (2).

00:00:00.00

00:00:00.00

Correlations

Control Variables stress

exercise & hardiness fitness Correlation


df

-.103

.048

369

comment estimates of unanalyzed association between exrercise and hardiness.

regression matrix=in(*)/variables=exercise,hardiness/dependent=hardiness/metho

d=enter/descriptives=cov corr.

Regression

Notes

Output Created

Comments

Input Filter

Weight

Split File


Matrix Input


Cases Used

Syntax


Elapsed Time

Memory Required

Additional Memory Required for Residual Plots

03-JAN-2015 21:07:12

<none>

<none>

<none>

8

working data file

User-defined missing values are treated as missing.Statistics are based on cases with no missing values for any variable used.regression matrix=in(*)/variables=exercise,hardiness/dependent=hardiness/method=enter/descriptives=cov corr.

00:00:00.00

00:00:00.01

4448 bytes

0 bytes

Correlations

exercise hardiness

Pearson Correlation exercise

hardiness

Covariance exercise

hardiness

1.000 -.030

-.030 1.000

4422.250 -75.810

-75.810 1444.000

Variables Entered/Removeda

ModelVariables Entered

Variables Removed Method

1 exerciseb . Enter

Dependent Variable: hardinessa.

All requested variables entered.b.

Model Summary

Model R R SquareAdjusted R

SquareStd. Error of the

Estimate

1 .030a .001 -.002 38.0340516

Predictors: (Constant), exercisea.

ANOVAa

ModelSum of Squares df Mean Square F Sig.

1 Regression

Residual

Total

483.451 1 483.451 .334 .564b

536684.549 371 1446.589

537168.000 372


Predictors: (Constant), exerciseb.

Coefficientsa

Model

Unstandardized CoefficientsStandardized Coefficients

t Sig.B Std. Error Beta

1 (Constant)

exercise

.000 1.969 .000 1.000

-.017 .030 -.030 -.578 .564


comment direct efects of exercise on fitness and of hardiness on stress.

regression matrix=in(*)/variables=exercise,fitness/dependent=fitness/method=en

ter.

Regression

Notes

Output Created

Comments

Input Filter

Weight

Split File


Matrix Input


Cases Used

Syntax


Elapsed Time

Memory Required


03-JAN-2015 21:07:12

<none>

<none>

<none>

8

working data file

User-defined missing values are treated as missing.Statistics are based on cases with no missing values for any variable used.regression matrix=in(*)/variables=exercise,fitness/dependent=fitness/method=enter.

00:00:00.00

00:00:00.01

4448 bytes

0 bytes




1 exerciseb . Enter

Dependent Variable: fitnessa.


Model Summary



Estimate

1 .390a .152 .150 16.9658122

Predictors: (Constant), exercisea.

ANOVAa


1 Regression

Residual

Total

19156.131 1 19156.131 66.552 .000b

106788.189 371 287.839

125944.320 372


Predictors: (Constant), exerciseb.

Coefficientsa

Model



1 (Constant)

exercise

.000 .878 .000 1.000

.108 .013 .390 8.158 .000


regression matrix=in(*)/variables=hardiness,stress/dependent=stress/method=ent

er.

Regression

Notes

Output Created

Comments

Input Filter

Weight

Split File


Matrix Input


Cases Used

Syntax


Elapsed Time

Memory Required


03-JAN-2015 21:07:12

<none>

<none>

<none>

8

working data file

User-defined missing values are treated as missing.Statistics are based on cases with no missing values for any variable used.regression matrix=in(*)/variables=hardiness,stress/dependent=stress/method=enter.

00:00:00.00

00:00:00.00

4448 bytes

0 bytes




1 hardinessb . Enter

Dependent Variable: stressa.


Model Summary



Estimate

1 .230a .053 .050 32.6457943

Predictors: (Constant), hardinessa.

ANOVAa


1 Regression

Residual

Total

22084.533 1 22084.533 20.722 .000b

395392.467 371 1065.748

417477.000 372


Predictors: (Constant), hardinessb.

Coefficientsa

Model



1 (Constant)

hardiness

.000 1.690 .000 1.000

-.203 .045 -.230 -4.552 .000


comment estimates of direct effect of fitness on illness.

comment sufficient set is exercise.

regression matrix=in(*)/variables=fitness,illness,exercise/dependent=illness/m

ethod=enter.

Regression

Notes

Output Created

Comments

Input Filter

Weight

Split File


Matrix Input


Cases Used

Syntax


Elapsed Time

Memory Required


03-JAN-2015 21:07:12

<none>

<none>

<none>

8

working data file

User-defined missing values are treated as missing.Statistics are based on cases with no missing values for any variable used.regression matrix=in(*)/variables=fitness,illness,exercise/dependent=illness/method=enter.

00:00:00.00

00:00:00.00

4672 bytes

0 bytes




1 exercise, fitnessb . Enter

Dependent Variable: illnessa.


Model Summary



Estimate

1 .292a .085 .080 59.9141072

Predictors: (Constant), exercise, fitnessa.

ANOVAa


1 Regression

Residual

Total

124006.059 2 62003.030 17.272 .000b

1328189.090 370 3589.700

1452195.149 372


Predictors: (Constant), exercise, fitnessb.

Coefficientsa

Model



1 (Constant)

fitness

exercise

.000 3.102 .000 1.000

-1.036 .183 -.305 -5.653 .000

.037 .051 .039 .723 .470


comment sufficient set is hardiness. regression matrix=in(*)/variables=fitness,illness,hardiness/dependent=illness/

method=enter.

Regression

Notes

Output Created

Comments

Input Filter

Weight

Split File


Matrix Input


Cases Used

Syntax


Elapsed Time

Memory Required


03-JAN-2015 21:07:12

<none>

<none>

<none>

8

working data file

User-defined missing values are treated as missing.Statistics are based on cases with no missing values for any variable used.regression matrix=in(*)/variables=fitness,illness,hardiness/dependent=illness/method=enter.

00:00:00.00

00:00:00.00

4672 bytes

0 bytes




1 hardiness, fitnessb . Enter



Model Summary



Estimate

1 .322a .104 .099 59.3110174

Predictors: (Constant), hardiness, fitnessa.

ANOVAa


1 Regression

Residual

Total

150610.339 2 75305.169 21.407 .000b

1301584.810 370 3517.797

1452195.149 372


Predictors: (Constant), hardiness, fitnessb.

Coefficientsa

Model



1 (Constant)

fitness

hardiness

.000 3.071 .000 1.000

-.951 .168 -.280 -5.679 .000

-.231 .081 -.140 -2.845 .005


comment sufficient is stress. regression matrix=in(*)/variables=fitness,illness,stress/dependent=illness/met

hod=enter.

Regression

Notes

Output Created

Comments

Input Filter

Weight

Split File


Matrix Input


Cases Used

Syntax


Elapsed Time

Memory Required


03-JAN-2015 21:07:12

<none>

<none>

<none>

8

working data file

User-defined missing values are treated as missing.Statistics are based on cases with no missing values for any variable used.regression matrix=in(*)/variables=fitness,illness,stress/dependent=illness/method=enter.

00:00:00.00

00:00:00.00

4672 bytes

0 bytes




1stress, fitnessb

. Enter



Model Summary



Estimate

1 .421a .177 .173 56.8324926

Predictors: (Constant), stress, fitnessa.

ANOVAa


1 Regression

Residual

Total

257120.228 2 128560.114 39.803 .000b

1195074.921 370 3229.932

1452195.149 372


Predictors: (Constant), stress, fitnessb.

Coefficientsa

Model



1 (Constant)

fitness

stress

.000 2.943 .000 1.000

-.849 .162 -.250 -5.257 .000

.574 .089 .307 6.465 .000


comment estimates of direct effect of stress on illness.


regression matrix=in(*)/variables=stress,illness,exercise/dependent=illness/me

thod=enter.

Regression

Notes

Output Created

Comments

Input Filter

Weight

Split File


Matrix Input


Cases Used

Syntax


Elapsed Time

Memory Required


03-JAN-2015 21:07:12

<none>

<none>

<none>

8

working data file

User-defined missing values are treated as missing.Statistics are based on cases with no missing values for any variable used.regression matrix=in(*)/variables=stress,illness,exercise/dependent=illness/method=enter.

00:00:00.02

00:00:00.00

4672 bytes

0 bytes




1 exercise, stressb . Enter



Model Summary



Estimate

1 .346a .120 .115 58.7836892

Predictors: (Constant), exercise, stressa.

ANOVAa


1 Regression

Residual

Total

173651.967 2 86825.984 25.127 .000b

1278543.182 370 3455.522

1452195.149 372


Predictors: (Constant), exercise, stressb.

Coefficientsa

Model



1 (Constant)

stress

exercise

.000 3.044 .000 1.000

.628 .091 .337 6.897 .000

-.059 .046 -.063 -1.293 .197


comment sufficient set is hardiness. regression matrix=in(*)/variables=stress,illness,hardiness/dependent=illness/m

ethod=enter.

Regression

Notes

Output Created

Comments

Input Filter

Weight

Split File


Matrix Input


Cases Used

Syntax


Elapsed Time

Memory Required


03-JAN-2015 21:07:12

<none>

<none>

<none>

8

working data file

User-defined missing values are treated as missing.Statistics are based on cases with no missing values for any variable used.regression matrix=in(*)/variables=stress,illness,hardiness/dependent=illness/method=enter.

00:00:00.00

00:00:00.00

4672 bytes

0 bytes




1 hardiness, stressb . Enter



Model Summary



Estimate

1 .350a .123 .118 58.6805752

Predictors: (Constant), hardiness, stressa.

ANOVAa


1 Regression

Residual

Total

178133.485 2 89066.742 25.866 .000b

1274061.664 370 3443.410

1452195.149 372


Predictors: (Constant), hardiness, stressb.

Coefficientsa

Model



1 (Constant)

stress

hardiness

.000 3.038 .000 1.000

.597 .093 .320 6.398 .000

-.142 .082 -.086 -1.726 .085


comment sufficient set is fitness. regression matrix=in(*)/variables=stress,illness,fitness/dependent=illness/met

hod=enter.

Regression

Notes

Output Created

Comments

Input Filter

Weight

Split File


Matrix Input


Cases Used

Syntax


Elapsed Time

Memory Required


03-JAN-2015 21:07:12

<none>

<none>

<none>

8

working data file

User-defined missing values are treated as missing.Statistics are based on cases with no missing values for any variable used.regression matrix=in(*)/variables=stress,illness,fitness/dependent=illness/method=enter.

00:00:00.00

00:00:00.00

4672 bytes

0 bytes




1fitness, stressb

. Enter



Model Summary



Estimate

1 .421a .177 .173 56.8324926

Predictors: (Constant), fitness, stressa.

ANOVAa


1 Regression

Residual

Total

257120.228 2 128560.114 39.803 .000b

1195074.921 370 3229.932

1452195.149 372


Predictors: (Constant), fitness, stressb.

Coefficientsa

Model



1 (Constant)

stress

fitness

.000 2.943 .000 1.000

.574 .089 .307 6.465 .000

-.849 .162 -.250 -5.257 .000


comment total effects of exercise on illness.

comment sufficient set is hardiness.

regression matrix=in(*)/variables=exercise,hardiness,illness/dependent=illness

/method=enter.

Regression

Notes

Output Created

Comments

Input Filter

Weight

Split File


Matrix Input


Cases Used

Syntax


Elapsed Time

Memory Required


03-JAN-2015 21:07:12

<none>

<none>

<none>

8

working data file

User-defined missing values are treated as missing.Statistics are based on cases with no missing values for any variable used.regression matrix=in(*)/variables=exercise,hardiness,illness/dependent=illness/method=enter.

00:00:00.00

00:00:00.00

4672 bytes

0 bytes




1 hardiness, exerciseb . Enter



Model Summary



Estimate

1 .181a .033 .028 61.6127126

Predictors: (Constant), hardiness, exercisea.

ANOVAa


1 Regression

Residual

Total

47628.396 2 23814.198 6.273 .002b

1404566.753 370 3796.126

1452195.149 372


Predictors: (Constant), hardiness, exerciseb.

Coefficientsa

Model



1 (Constant)

exercise

hardiness

.000 3.190 .000 1.000

-.080 .048 -.085 -1.659 .098

-.267 .084 -.163 -3.178 .002


comment sufficient set is stress. regression matrix=in(*)/variables=exercise,stress,illness/dependent=illness/me

thod=enter.

Regression

Notes

Output Created

Comments

Input Filter

Weight

Split File


Matrix Input


Cases Used

Syntax


Elapsed Time

Memory Required


03-JAN-2015 21:07:12

<none>

<none>

<none>

8

working data file

User-defined missing values are treated as missing.Statistics are based on cases with no missing values for any variable used.regression matrix=in(*)/variables=exercise,stress,illness/dependent=illness/method=enter.

00:00:00.00

00:00:00.00

4672 bytes

0 bytes




1 stress, exerciseb . Enter



Model Summary



Estimate

1 .346a .120 .115 58.7836892

Predictors: (Constant), stress, exercisea.

ANOVAa


1 Regression

Residual

Total

173651.967 2 86825.984 25.127 .000b

1278543.182 370 3455.522

1452195.149 372


Predictors: (Constant), stress, exerciseb.

Coefficientsa

Model



1 (Constant)

exercise

stress

.000 3.044 .000 1.000

-.059 .046 -.063 -1.293 .197

.628 .091 .337 6.897 .000


comment total effects of hardiness on illness.


regression matrix=in(*)/variables=hardiness,exercise,illness/dependent=illness

/method=enter.

Regression

Notes

Output Created

Comments

Input Filter

Weight

Split File


Matrix Input


Cases Used

Syntax


Elapsed Time

Memory Required


03-JAN-2015 21:07:12

<none>

<none>

<none>

8

working data file

User-defined missing values are treated as missing.Statistics are based on cases with no missing values for any variable used.regression matrix=in(*)/variables=hardiness,exercise,illness/dependent=illness/method=enter.

00:00:00.02

00:00:00.01

4672 bytes

0 bytes




1 exercise, hardinessb . Enter



Model Summary



Estimate

1 .181a .033 .028 61.6127126

Predictors: (Constant), exercise, hardinessa.

ANOVAa


1 Regression

Residual

Total

47628.396 2 23814.198 6.273 .002b

1404566.753 370 3796.126

1452195.149 372


Predictors: (Constant), exercise, hardinessb.

Coefficientsa

Model



1 (Constant)

hardiness

exercise

.000 3.190 .000 1.000

-.267 .084 -.163 -3.178 .002

-.080 .048 -.085 -1.659 .098


comment sufficient set is fitness. regression matrix=in(*)/variables=hardiness,fitness,illness/dependent=illness/

method=enter.

Regression

Notes

Output Created

Comments

Input Filter

Weight

Split File


Matrix Input


Cases Used

Syntax


Elapsed Time

Memory Required


03-JAN-2015 21:07:12

<none>

<none>

<none>

8

working data file

User-defined missing values are treated as missing.Statistics are based on cases with no missing values for any variable used.regression matrix=in(*)/variables=hardiness,fitness,illness/dependent=illness/method=enter.

00:00:00.00

00:00:00.01

4672 bytes

0 bytes




1 fitness, hardinessb . Enter



Model Summary



Estimate

1 .322a .104 .099 59.3110174

Predictors: (Constant), fitness, hardinessa.

ANOVAa


1 Regression

Residual

Total

150610.339 2 75305.169 21.407 .000b

1301584.810 370 3517.797

1452195.149 372


Predictors: (Constant), fitness, hardinessb.

Coefficientsa

Model



1 (Constant)

hardiness

fitness

.000 3.071 .000 1.000

-.231 .081 -.140 -2.845 .005

-.951 .168 -.280 -5.679 .000


partial corr matrix = in ( * ) / variables = exercise …correlations control variables stress...

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