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?
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
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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