7. Refit the model but instead of using BMI as a continuous variable, use the indicator variables for the CDC's descriptive categories of weight. Interpret the results in the context of the problem. Include test statistics and 95% confidence intervals in your interpretation. In this model with indicator variables for BMI, test for the significance of BMI. (5 pts)

proc phreg data=hw7.comprisk; class BMI_1 BMI_2 BMI_3; model Time*Status(0) = BMI_1 BMI_2 BMI_3 Sex / ties=EFRON rl; id ID; run;

proc phreg data=hw7.comprisk; model Time*Status(0) = BMI_1 BMI_2 BMI_3 Age Sex; run;

SAS code? 8. Evaluate the proportional hazards assumption for the full model you fit in question 7. Interpret the results for each of the variables individually and globally. What do you conclude?