Quality and Reliability Methods - SAS

390 Reliability and Survival Analysis II Chapter 20
Proportional Hazards Model
For this example, the risk ratio for Group2/Group1 is calculated as
exp[-(-0.2979479)] /exp(-0.2979479) = 1.8146558
This risk ratio value suggests that the risk of death for Group 2 is 1.82 times higher than that for
Group 1.
Figure 20.18 Risk Ratios for Group Table
See “Calculating Risk Ratios for Multiple Effects and Multiple Levels” on page 393 for a description of how
risk ratios are calculated when there are multiple effects and for categorical effects with more than two levels.
Example: Multiple Effects and Multiple Levels
This example uses a proportional hazards model for the sample data, VA Lung Cancer.jmp. The data were
collected from a randomized clinical trial, where males with inoperable lung cancer were placed on either a
standard or a novel (test) chemotherapy (Treatment). The primary interest of this trial was to assess if the
treatment type has an effect on survival time, with special interest given to the type of tumor (Cell Type).
See Prentice (1973) and Kalbfleisch and Prentice (2002) for additional details regarding this data set. For
the proportional hazards model, covariates include whether or not the patient had undergone previous
therapy (Prior), the age of the patient (Age), the time from lung cancer diagnosis to beginning the study
(Diag Time), and a general medical status measure (KPS). Age, Diag Time, and KPS are continuous
measures and Cell Type, Treatment, and Prior are categorical (nominal) variables. The four nominal levels
of Cell Type include Adeno, Large, Small, and Squamous.
This section illustrates the report window for a model with more than one effect and a nominal effect with
more than two levels. This section also includes example calculations for risk ratios for a continuous effect
and risk ratios for an effect that has more than two levels.
1. Open the sample data, VA Lung Cancer.jmp.
2. Select Analyze > Reliability and Survival > Fit Proportional Hazards.
3. Select Time as Time to Event.
4. Select censor as Censor.
5. Select Cell Type, Treatment, Prior, Age, Diag Time, and KPS as the model effects.
Figure 20.19 shows the completed launch window.