SAS 9.2 brings a number of new procedures to SAS/STAT software. Several of these procedures have been previously available as Web downloads for SAS 9.1.3: GLIMMIX, GLMSELECT, and QUANTREG. The GLMSELECT procedure performs effect selection in the framework of general linear models. The QUANTREG procedure performs quantile regression. The GLIMMIX procedure analyzes generalized linear mixed models. All of these procedures are production with SAS 9.2 and are available on all platforms.

In addition, Bayesian capabilities were introduced to three procedures via Web downloads for SAS 9.1.3. The BGENMOD, BLIFEREG, and BPHREG procedures were experimental versions of the GENMOD, LIFEREG, and PHREG procedures that used the Gibbs sampler to produce posterior distributions while also providing trace plots and convergence diagnostics. These capabilities have been rolled into the GENMOD, LIFEREG, and PHREG procedures for SAS 9.2 and are now production software.

The MCMC, SEQDESIGN, and SEQTEST procedures were introduced as experimental procedures in SAS 9.2, and they became production in SAS 9.2M2.

The MCMC procedure is a general purpose Markov chain Monte Carlo (MCMC) simulation procedure that is designed to fit a variety of Bayesian models. You specify a likelihood function for the data and a prior distribution for the parameters. PROC MCMC obtains samples from the corresponding posterior distributions, produces summary and diagnostic statistics, and saves the posterior samples in an output data set.

The SEQDESIGN and SEQTEST procedures are tools for group sequential analysis. The SEQDESIGN procedure designs interim analyses for clinical trials, and the SEQTEST procedure performs interim analyses.

The experimental HPMIXED procedure uses a number of specialized high-performance techniques to fit linear mixed models with variance component structure. The HPMIXED procedure is specifically designed to cope with estimation problems that involve a large number of fixed effects, a large number of random effects, or a large number of observations. The models supported by the HPMIXED procedure are a subset of the models that you can fit with the MIXED procedure, and PROC HPMIXED can provide substantial performance improvements in terms of memory requirements and computational speed.

The experimental TCALIS procedure updates the CALIS procedure for structural equation modeling. It will become the CALIS procedure in the next release of SAS/STAT software.