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GET

FILE='C:\Users\Pavitra\Documents\Logistic Regression Analysis data.sav'.

DATASET NAME DataSet3 WINDOW=FRONT.

LOGISTIC REGRESSION VARIABLES VAR00004

/METHOD=ENTER VAR00001 VAR00002 VAR00003

/SAVE=PRED PGROUP

/PRINT=GOODFIT/CRITERIA=PIN(0.05) POUT(0.10) ITERATE(20) CUT(0.5).

Logistic Regression

Notes

Output Created 23-SEP-2013 12:19:48

Comments

Input

DataC:\Users\Pavitra\Documents\Logistic

Regression Analysis data.sav

Active Dataset DataSet3

Filter

Weight

Split File

N of Rows in Working

Data File

18

Missing Value Handling Definition of MissingUser-defined missing values are

treated as missing

Syntax

LOGISTIC REGRESSION

VARIABLES VAR00004

/METHOD=ENTER VAR00001

VAR00002 VAR00003

/SAVE=PRED PGROUP

/PRINT=GOODFIT

/CRITERIA=PIN(0.05) POUT(0.10)

ITERATE(20) CUT(0.5).

ResourcesProcessor Time 00:00:00.02

Elapsed Time 00:00:00.02

Variables Created or

Modified

PRE_2 Predicted probability

PGR_2 Predicted group

[DataSet3] C:\Users\Pavitra\Documents\Logistic Regression Analysis data.sav

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Case Processing Summary

Unweighted Casesa N Percent

Selected Cases

Included in Analysis 18 100.0

Missing Cases 0 .0

Total 18 100.0

Unselected Cases 0 .0

Total 18 100.0

a. If weight is in effect, see classification table for the total number

of cases.

Dependent Variable Encoding

Original Value Internal Value

.00 0

1.00 1

Block 0: Beginning Block

Classification Tablea,b

Observed Predicted

IndiaWin Percentage

Correct.00 1.00

Step

0

IndiaWi

n

.00 0 9 .0

1.00 0 9 100.0

Overall Percentage 50.0

a. Constant is included in the model.

b. The cut value is .500

Variables in the Equation

B S.E. Wald df Sig. Exp(B)

Step

0

Constan

t

.000 .471 .000 1 1.000 1.000

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Variables not in the Equation

Score df Sig.

Step

0

Variables

VAR0000

1

2.166 1 .141

VAR0000

2

2.000 1 .157

VAR0000

3

1.655 1 .198

Overall Statistics 6.237 3 .101

Block 1: Method = Enter

Omnibus Tests of Model Coefficients

Chi-square df Sig.

Step

1

Step 7.543 3 .056

Block 7.543 3 .056

Mod

el

7.543 3 .056

Model Summary

Step -2 Log

likelihood

Cox & Snell R

Square

Nagelkerke R

Square

1 17.410a .342 .456

a. Estimation terminated at iteration number 5 because

parameter estimates changed by less than .001.

Hosmer and Lemeshow Test

Step Chi-square df Sig.

1 8.555 7 .286

Contingency Table for Hosmer and Lemeshow Test

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IndiaWin = .00 IndiaWin = 1.00 Total

Observe

d

Expecte

d

Observe

d

Expecte

d

Step

1

1 2 1.931 0 .069 2

2 1 1.756 1 .244 2

3 1 1.382 1 .618 2

4 2 1.093 0 .907 2

5 1 1.053 1 .947 2

6 2 .862 0 1.138 2

7 0 .545 2 1.455 2

8 0 .258 2 1.742 2

9 0 .120 2 1.880 2

Classification Tablea

Observed Predicted

IndiaWin Percentage

Correct.00 1.00

Step

1

IndiaWi

n

.00 8 1 88.9

1.00 3 6 66.7

Overall Percentage 77.8

a. The cut value is .500

Variables in the Equation

B S.E. Wald df Sig. Exp(B)

Step

1a

VAR0000

1

.043 .023 3.389 1 .066 1.044

VAR0000

2

-1.854 1.548 1.434 1 .231 .157

VAR0000

3

.661 .640 1.066 1 .302 1.936

Constant -2.708 2.180 1.544 1 .214 .067

a. Variable(s) entered on step 1: VAR00001, VAR00002, VAR00003.