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Chapter 6. Competing Risks > ACCELERATED FAILURE TIME MODELS

ACCELERATED FAILURE TIME MODELS

Competing risks analysis with accelerated failure time models is basically the same as with Cox models. As before, the key point is to treat all events as censoring except the one that you're focusing on. However, there are some complications that arise in constructing tests of equality of coefficients across event types. There are also some special characteristics of the LEADER data set that require slightly different treatment with accelerated failure time models.

One of those characteristics is the presence of 0s in the YEARS variable. Recall that any leaders who served less than 1 year were assigned a time value of 0. Of the 472 leaders, 106 fell in this category. This poses no problem for PROC PHREG, which is only concerned with the rank order of the time variable. On the other hand, PROC LIFEREG excludes any observations with times of 0 or less because it must take the logarithm of the event time as the first step. But we certainly don't want to exclude 22 percent of the cases. One approach is to assign some arbitrarily chosen number between 0 and 1. A more elegant solution is to treat such cases as if they were left censored at time 1. We discussed how to do this in some detail in the section Left Censoring and Interval Censoring in Chapter 4, "Estimating Parametric Regression Models with PROC LIFEREG." For the LEADER data set, we need a short DATA step to create LOWER and UPPER variables that are appropriately coded. Here's how to prepare the data set for modeling the constitutional exits.


  

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