What odds ratio does exp(?) represent in Model 1? What odds ratio does exp(?) represent in Model 2? b. Using Model 1, if a child has a 5-minute Apgar score of 3, what is the predicted probability that the child will experience a germinal matrix hemorrhage? c. Using Model 3, if a child has a 5-minute Apgar score of 7 and the child is female, what is the predicted probability that the child will experience a germinal matrix hemorrhage? d. Test the null hypothesis that the coefficient associated with 5-minute Apgar score is 0 after controlling for sex. e. Which model do you prefer for predicting germinal matrix hemorrhage and why?

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Data were collected on 100 low birthweight infants. The variable grmhem is a binary variable indicating whether the infant experienced a germinal matrix hemorrhage (1 = yes and 0 = no). The variable apgar5 contains 5-minute Apgar scores (treat as continuous) and the variable sex contains sex of the infant (1 = male and 0 = female). SAS output is included below for 3 different models with germinal matrix hemorrhage as the outcome
variable. Model 1 includes 5-minute Apgar score as the only predictor, Model 2 includes sex as the only predictor, and Model 3 includes both 5-minute Apgar score and sex as predictors.

 

a. What odds ratio does exp(?) represent in Model 1? What odds ratio does exp(?) represent in Model 2?
b. Using Model 1, if a child has a 5-minute Apgar score of 3, what is the predicted probability that the child will experience a germinal matrix hemorrhage?
c. Using Model 3, if a child has a 5-minute Apgar score of 7 and the child is female, what is the predicted probability that the child will experience a germinal matrix hemorrhage?
d. Test the null hypothesis that the coefficient associated with 5-minute Apgar score is 0 after controlling for sex.
e. Which model do you prefer for predicting germinal matrix hemorrhage and why?

 

Model 1:
ROC Curve for Model
Area Under the Curve = 0.7282
Testing Global Null Hypothesis: BETA=0
1.00
Test
Chi-Square DF Pr> ChiSq
Likelihood Ratio
5.6150
1
0.0178
Score
6.3451
0.0118
0.75
Wald
5.7206
0.0168
Analysis of Maximum Likelihood Estimates
0.50
Standard
Error Chi-Square Pr> Chisq
Wald
Parameter DF Estimate
Intercept
1 -0.3037
0.6191
0.2407
0.6237
apgar5
1 -0.2496
0.1044
5.7206
0.0168
025
5
Odds Ratio Estimates
95% Wald
Point Estimate Confidence Limits
0.00
Effect
0.00
025
050
0.75
1.00
apgar5
0.779
0.635
0.956
1- Specificity
Model 2:
ROC Curve for Model
Area Under the Curve = 0.6020
Testing Global Null Hypothesis: BETA=0
1.00
Test
Chi-Square DF Pr> Chisq
Likelihood Ratio
2.2478
1
0.1338
Score
2.1518
0.1424
0.75
Wald
2.0583
1
0.1514
Analysis of Maximum Likelihood Estimates
0.50
Standard
Wald
Parameter DF Estimate
Error Chi-Square Pr> Chisq
1
1 -0.8938
Intercept
-1.4088
0.3363
17.5427
<.0001
025
sex
0.6230
2.0583
0.1514
Odds Ratio Estimates
0.00
95% Wald
Effect Point Estimate Confidence Limits
0.00
0.25
0.50
0.75
1.00
0.409
0.121
1.387
1- Specificity
sex
Sensitivity
Transcribed Image Text:Model 1: ROC Curve for Model Area Under the Curve = 0.7282 Testing Global Null Hypothesis: BETA=0 1.00 Test Chi-Square DF Pr> ChiSq Likelihood Ratio 5.6150 1 0.0178 Score 6.3451 0.0118 0.75 Wald 5.7206 0.0168 Analysis of Maximum Likelihood Estimates 0.50 Standard Error Chi-Square Pr> Chisq Wald Parameter DF Estimate Intercept 1 -0.3037 0.6191 0.2407 0.6237 apgar5 1 -0.2496 0.1044 5.7206 0.0168 025 5 Odds Ratio Estimates 95% Wald Point Estimate Confidence Limits 0.00 Effect 0.00 025 050 0.75 1.00 apgar5 0.779 0.635 0.956 1- Specificity Model 2: ROC Curve for Model Area Under the Curve = 0.6020 Testing Global Null Hypothesis: BETA=0 1.00 Test Chi-Square DF Pr> Chisq Likelihood Ratio 2.2478 1 0.1338 Score 2.1518 0.1424 0.75 Wald 2.0583 1 0.1514 Analysis of Maximum Likelihood Estimates 0.50 Standard Wald Parameter DF Estimate Error Chi-Square Pr> Chisq 1 1 -0.8938 Intercept -1.4088 0.3363 17.5427 <.0001 025 sex 0.6230 2.0583 0.1514 Odds Ratio Estimates 0.00 95% Wald Effect Point Estimate Confidence Limits 0.00 0.25 0.50 0.75 1.00 0.409 0.121 1.387 1- Specificity sex Sensitivity
Testing Global Null Hypothesis: BETA=0
ROC Curve for Model
Test
Chi-Square
DF
Pr > ChiSq
Area Under the Curve = 0.7643
Likelihood Ratio
7.5762
2
0.0226
1.00
Score
8.1478
2
0.0170
Wald
7.1446
2
0.0281
0.75
Analysis of Maximum Likelihood Estimates
Standard
Wald
Parameter
DF
Estimate
Error
Chi-Square Pr> ChiSq
0.50
Intercept
1
-0.0134
0.6596
0.0004
0.9838
apgar5
1
-0.2451
0.1056
5.3927
0.0202
sex
1
-0.8622
0.6399
1.8152
0.1779
0.25
Odds Ratio Estimates
95% Wald
Effect
Point Estimate
Confidence Limits
0.00
apgar5
0.783
0.636
0.962
0.00
0.25
0.50
0.75
1.00
0.422
0.120
1.480
1- Specificity
sex
Sensitivity
Transcribed Image Text:Testing Global Null Hypothesis: BETA=0 ROC Curve for Model Test Chi-Square DF Pr > ChiSq Area Under the Curve = 0.7643 Likelihood Ratio 7.5762 2 0.0226 1.00 Score 8.1478 2 0.0170 Wald 7.1446 2 0.0281 0.75 Analysis of Maximum Likelihood Estimates Standard Wald Parameter DF Estimate Error Chi-Square Pr> ChiSq 0.50 Intercept 1 -0.0134 0.6596 0.0004 0.9838 apgar5 1 -0.2451 0.1056 5.3927 0.0202 sex 1 -0.8622 0.6399 1.8152 0.1779 0.25 Odds Ratio Estimates 95% Wald Effect Point Estimate Confidence Limits 0.00 apgar5 0.783 0.636 0.962 0.00 0.25 0.50 0.75 1.00 0.422 0.120 1.480 1- Specificity sex Sensitivity
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