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CE_30T Wed, 7/31/2019, 8:00 AM - 9:45 AM CC-403/404
Introducing the SAS BGLIMM Procedure for Bayesian Generalized Linear Mixed Models (ADDED FEE) — Professional Development Computer Technology Workshop
ASA, SAS
SAS/STAT® 15.1 includes PROC BGLIMM, a new, high-performance, sampling-based procedure that provides full Bayesian inference for generalized linear mixed models (GLMMs). PROC BGLIMM models data from the exponential family distributions that have correlations or nonconstant variability; uses syntax similar to that of the MIXED and GLIMMIX procedures (the CLASS, MODEL, RANDOM, REPEATED, and ESTIMATE statements); deploys optimal sampling algorithms that are parallelized for performance; handles multilevel nested and non-nested random-effects models; and fits models to multivariate or longitudinal data with repeated measurements. PROC BGLIMM provides convenient access, with improved performance, to Bayesian analysis of complex mixed models that you could previously perform with the MCMC procedure. This workshop starts with a general discussion of Bayesian GLMM, then presents the important features of PROC BGLIMM, showing you how to use it for estimation, inference, and prediction.
Instructor(s): Amy Shi, SAS Institute Inc