PHREG Procedure

The PHREG procedure now supports the ESTIMATE, LSMEANS, LSMESTIMATE, and SLICE statements for additional postfitting inferences.

The experimental EFFECT statement enables you to construct a much richer family of linear models than you can traditionally define with the CLASS statement. The STORE statement enables you to save the context and results of the statistical analysis for further processing with the PLM procedure.

The ATRISK option in the PROC PHREG statement displays a table that contains the number of units at risk at each event time and the corresponding number of events in the risk sets.

You can now specify the Zellner g-prior for the regression coefficients in the BAYES statement. You can also request the random walk Metropolis (RWM) algorithm to sample an entire parameter vector from the posterior distribution in a Bayesian analysis.

Likelihood ratio tests of model parameters are available with the TYPE1 and TYPE3 options in the MODEL statement except when the robust sandwich estimate for the covariance matrix is specified.