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Overview: This paper describes a new SAS/STAT procedure for fitting models to non-normal or normal data with connection or no constant variability. PROC GLIMMIX extends the SAS mixed model tools in a number of ways. Applications of the GLIMMIX procedure include estimating trends in disease rates, modeling counts or proportions over time in a clinical trial, predicting probability of occurrence in time series and spatial data, and joint modeling of correlated binary and continuous data. This paper describes generalized linear mixed models and how to use the GLIMMIX procedure for estimation, inference, and prediction.
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