LIFEREG Procedure
The LIFEREG procedure fits parametric models to failure time data that can be uncensored, right censored, left censored, or
interval censored. The models for the response variable consist of a linear effect composed of the covariates and a random
disturbance term. The distribution of the random disturbance can be taken from a class of distributions that includes the
extreme value, normal, logistic, and, by using a log transformation, the exponential, Weibull, lognormal, loglogistic, and
threeparameter gamma distributions. The following are highlights of the LIFEREG procedure's features:
 estimates the parameters by maximum likelihood with a NewtonRaphson
algorithm
 estimates the standard errors of the parameter estimates from the
inverse of the observed information matrix
 fits an accelerated failure time model that assumes that the effect
of independent variables on an event time distribution is multiplicative
on the event time
 computes least square means and least square mean differences for classification effects
 performs multiple comparison adjustments for the pvalues and confidence limits for the least
square mean differences
 estimates linear functions of the model parameters

 tests hypotheses for linear combinations of the model parameters
 performs samplingbased Bayesian analysis
 performs weighted estimation
 performs BY group processing, which enables you to obtain separate analyses on grouped observations
 creates a SAS data set that contains the parameter estimates, the maximized log likelihood,
and the estimated covariance matrix
 creates a SAS data set that corresponds to any output table
 automatically creates graphs by using ODS Graphics

For further details see the LIFEREG Procedure
Examples