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Logistic Regression: Case Processing Summary

This document summarizes the results of a logistic regression analysis examining factors that predict hypertension. It provides information on case processing, variable coding, classification tables, odds ratios, and tests of model fit. Key results include that high consumption of saturated fat and normal salt intake significantly predict hypertension, while physical activity was not a significant predictor when added to the model. The analysis identified a model with two significant predictors that correctly classified 95% of hypertension cases and 45.5% of non-hypertension cases.

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Nabila Saribanun
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85 views4 pages

Logistic Regression: Case Processing Summary

This document summarizes the results of a logistic regression analysis examining factors that predict hypertension. It provides information on case processing, variable coding, classification tables, odds ratios, and tests of model fit. Key results include that high consumption of saturated fat and normal salt intake significantly predict hypertension, while physical activity was not a significant predictor when added to the model. The analysis identified a model with two significant predictors that correctly classified 95% of hypertension cases and 45.5% of non-hypertension cases.

Uploaded by

Nabila Saribanun
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as RTF, PDF, TXT or read online on Scribd
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Logistic Regression

Case Processing Summary


Unweighted Casesa N Percent
Selected Cases Included in Analysis 31 100.0
Missing Cases 0 .0
Total 31 100.0
Unselected Cases 0 .0
Total 31 100.0

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


cases.

Dependent Variable Encoding


Original Value Internal Value
Ya 0
Tidak 1

Categorical Variables Codings


Parameter
coding
Frequency (1)
Aktivitas_Fisik Ya 16 1.000
Tidak 15 .000
Konsumsi_Garam Tinggi 18 1.000
Normal 13 .000

Classification Tablea,b
Predicted
Hipertensi Percentage
Observed Ya Tidak Correct
Step 0 Hipertensi Ya 20 0 100.0
Tidak 11 0 .0
Overall Percentage 64.5

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 Constant -.598 .375 2.536 1 .111 .550

Variables not in the Equation


Score df Sig.
Step 0 Variables Konsumsi_Garam(1) 6.639 1 .010
Konsumsi_Lemak_Jenuh 7.682 1 .006
Aktivitas_Fisik(1) 4.045 1 .044
Overall Statistics 12.041 3 .007
Block 1: Method = Backward Stepwise (Likelihood Ratio)
Omnibus Tests of Model Coefficients
Chi-square df Sig.
Step 1 Step 13.372 3 .004
Block 13.372 3 .004
Model 13.372 3 .004
Step 2a Step -.881 1 .348
Block 12.492 2 .002
Model 12.492 2 .002

a. A negative Chi-squares value indicates that the Chi-squares


value has decreased from the previous step.

Model Summary
Cox & Snell R Nagelkerke R
Step -2 Log likelihood Square Square
1 26.952a .350 .481
2 27.833a .332 .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 3.762 5 .584
2 .116 2 .944

Contingency Table for Hosmer and Lemeshow Test


Hipertensi = Ya Hipertensi = Tidak Total
Observed Expected Observed Expected
Step 1 1 10 9.389 0 .611 10
2 3 3.399 1 .601 4
3 2 1.521 0 .479 2
4 1 1.843 2 1.157 3
5 2 2.692 3 2.308 5
6 1 .617 1 1.383 2
7 1 .540 4 4.460 5
Step 2 1 13 12.828 1 1.172 14
2 4 4.172 3 2.828 7
3 2 2.172 2 1.828 4
4 1 .828 5 5.172 6

Classification Tablea
Predicted
Hipertensi Percentage
Observed Ya Tidak Correct
Step 1 Hipertensi Ya 18 2 90.0
Tidak 6 5 45.5
Overall Percentage 74.2
Step 2 Hipertensi Ya 19 1 95.0
Tidak 6 5 45.5
Overall Percentage 77.4
a. The cut value is .500

Variables in the Equation

B S.E. Wald df Sig.


Step 1a Konsumsi_Garam(1) -1.578 1.057 2.227 1 .136
Konsumsi_Lemak_Jenuh 2.266 1.023 4.904 1 .027
Aktivitas_Fisik(1) -1.000 1.073 .869 1 .351
Constant -2.420 1.469 2.715 1 .099
Step 2a Konsumsi_Garam(1) -2.004 .966 4.303 1 .038
Konsumsi_Lemak_Jenuh 2.221 .991 5.016 1 .025
Constant -2.609 1.439 3.287 1 .070

Variables in the Equation


95% C.I.for EXP(B)
Exp(B) Lower Upper
Step 1a Konsumsi_Garam(1) .206 .026 1.639
Konsumsi_Lemak_Jenuh 9.640 1.297 71.625
Aktivitas_Fisik(1) .368 .045 3.011
Constant .089
Step 2a Konsumsi_Garam(1) .135 .020 .895
Konsumsi_Lemak_Jenuh 9.213 1.320 64.324
Constant .074

a. Variable(s) entered on step 1: Konsumsi_Garam, Konsumsi_Lemak_Jenuh, Aktivitas_Fisik.

Model if Term Removed


Model Log Change in -2 Sig. of the
Variable Likelihood Log Likelihood df Change
Step 1 Konsumsi_Garam -14.648 2.344 1 .126
Konsumsi_Lemak_Jenuh -16.304 5.656 1 .017
Aktivitas_Fisik -13.916 .881 1 .348
Step 2 Konsumsi_Garam -16.334 4.835 1 .028
Konsumsi_Lemak_Jenuh -16.772 5.711 1 .017

Variables not in the Equation


Score df Sig.
Step 2a Variables Aktivitas_Fisik(1) .902 1 .342
Overall Statistics .902 1 .342

a. Variable(s) removed on step 2: Aktivitas_Fisik.

FREQUENCIES VARIABLES=Konsumsi_Lemak_Jenuh
/ORDER=ANALYSIS.

Case Processing Summary


Cases
Valid Missing Total
N Percent N Percent N Percent
Hipertensi *
31 100.0% 0 0.0% 31 100.0%
Konsumsi_Lemak_Jenuh

Hipertensi * Konsumsi_Lemak_Jenuh Crosstabulation


Konsumsi_Lemak_Jenuh
Ya Tidak Total
Hipertensi Ya Count 17 3 20
Expected Count 13.5 6.5 20.0
Tidak Count 4 7 11
Expected Count 7.5 3.5 11.0
Total Count 21 10 31
Expected Count 21.0 10.0 31.0

Chi-Square Tests
Asymp. Sig. (2- Exact Sig. (2- Exact Sig. (1-
Value df sided) sided) sided)
Pearson Chi-Square 7.682a 1 .006
b
Continuity Correction 5.618 1 .018
Likelihood Ratio 7.657 1 .006
Fisher's Exact Test .013 .009
N of Valid Cases 31

a. 1 cells (25.0%) have expected count less than 5. The minimum expected count is 3.55.
b. Computed only for a 2x2 table

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