PLEASE SOLVE PROBLEM USING SAS

SAS DATA SET WILL BE LISTED AT END TO BE COPIED TO A TEXT FILE AND UPLOADED TO SAS

PLEASE SHOW ALL CODE AND OUTPU

- (a) Do 1(b) and 1(c)

1(b) Form a scatterplot of STA versus AGE.

1(c) Using the intervals (15, 24), (25, 34), (35, 44), (45, 54), (55, 64), (65, 74), (75, 84), (85, 94) for age, compute the STA mean over subjects within each age interval. Plot these values of mean STA versus the midpoint of the age interval using the same set of axes as was used in 1(b). (Note: this plot may done "by hand" on a printed copy of the plot from 1(b).)

-(b) Fit a logistic regression of STA on AGE. (In particular, fit a model which predicts the probability a subject Lived (STA = 1) as a function AGE.) Include the table of Maximum Likelihood Estimates from the output in your homework.

-(c) Test for the significance of the coefficient for AGE. (Include the relevant output in your homework.) State the conclusion and interpret the result. Comment on the similarities or the differences between the different significance tests which are available in your statistical package.

-(d) Obtain a 95% confidence interval for the coefficient for AGE. (Include the relevant output in your homework.) Comment on the similarities or the differences between the different confidence intervals available in your statistical package.

-(e) Compute the predicted probabilities of STA = 1 (Lived) for all subjects. Include the values for the first 10 subjects in your homework. Write down the equation for the predicted probabilities from your fitted model. Plot the predicted probabilities versus AGE for all subjects. Also construct a graph which superimposes the plot of the predicted probabilities on the plot of the grouped estimates obtained earlier in part (a).

-(f) Based on your fitted logistic regression model, give estimates of the logit (also known as the linear predictor) and the probability of a response (STA = 1) for an 86-year old subject. Also give 95% confidence intervals for both these quantities. (Use your stat package to compute as much of the calculations as possible.)

"id" "sta" "age" "gender" "race" "ser" "can" "crn" "inf" "cpr" "sys" "hra" "pre" "type" "fra" "po2" "ph" "pco" "bic" "cre" "loc" 4 0 87 1 1 1 0 0 1 0 80 96 0 1 1 1 1 1 0 0 0 8 1 27 1 1 0 0 0 1 0 142 88 0 1 0 0 0 0 0 0 0 12 1 59 0 1 0 0 0 0 0 112 80 1 1 0 0 0 0 0 0 0 14 1 77 0 1 1 0 0 0 0 100 70 0 0 0 0 0 0 0 0 0 27 0 76 1 1 1 0 0 1 0 128 90 1 1 0 0 0 0 0 0 0 28 1 54 0 1 0 0 0 1 0 142 103 0 1 1 0 0 0 0 0 0 32 1 87 1 1 1 0 0 1 0 110 154 1 1 0 0 0 0 0 0 0 38 1 69 0 1 0 0 0 1 0 110 132 0 1 0 1 0 0 1 0 0 40 1 63 0 1 1 0 0 0 0 104 66 0 0 0 0 0 0 0 0 0 41 1 30 1 1 0 0 0 0 0 144 110 0 1 0 0 0 0 0 0 0 42 1 35 0 2 0 0 0 0 0 108 60 0 1 0 0 0 0 0 0 0 47 0 78 0 1 0 0 0 1 0 130 132 0 1 0 0 0 0 1 0 0 50 1 70 1 1 1 1 0 0 0 138 103 0 0 0 0 0 0 0 0 0 51 1 55 1 1 1 0 0 1 0 188 86 1 0 0 0 0 0 0 0 0 52 0 63 0 1 0 0 1 1 0 112 106 1 1 0 1 0 0 0 0 0 53 1 48 0 2 1 1 0 0 0 162 100 0 0 0 0 0 0 0 0 0 58 1 66 1 1 1 0 0 0 0 160 80 1 0 0 0 0 0 0 0 0 61 1 61 1 1 0 0 1 0 0 174 99 0 1 0 0 1 0 1 1 0 73 1 66 0 1 0 0 0 0 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