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Unformatted text preview: the stomach cancer example, where survivor curves crossed: 20 Testing the proportional hazards assumption The proportional hazards assumption is that the ratio of hazards is a constant that
does not depend on time: h A (t )
h B (t ) When this assumption fails, it is because the hazard ratio changes over time.
To test this, add predictor for group*time interaction.
Evidence that group*time interaction is not zero is evidence against proportional
hazards. 21 Breast cancer example: groups are positive_stain = 0, 1,
response time = surv_months.
group*time interaction: positive_stain * surv_months? Interaction combines response and predictor! Predictors that change with time are deﬁned inside PHreg not in a DATA step. Proc PHreg data=breast_cancer;
model surv_months * died(0) = positive_stain PS_time
/ risklimits ties=efron;
PS_time = positive_stain * surv_months; 22 Breast cancer example:
Parameter Standard DF Estimate Error Chi-Square Pr > ChiSq positive_stain 0 1 -1.88112 0.98093 3.6775 0.0551 PS_time 1 -0.01371 0.01070 1.6...
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- Fall '11