SAS/STAT software provides comprehensive statistical tools for a wide range of statistical analyses, including analysis of variance, categorical data analysis, cluster analysis, multiple imputation, multivariate analysis, nonparametric analysis, power and sample size computations, psychometric analysis, regression, survey data analysis, and survival analysis. A few examples include nonlinear mixed models, generalized linear models, correspondence analysis, and robust regression. The software is constantly being updated to reflect new methodology. SAS/STAT software provides more than 90 procedures for statistical analysis.
SAS/STAT software also provides high-performance predictive modeling tools that have been specially developed to take advantage of parallel processing in multithreaded single-machine mode. Predictive modeling methods include regression, logistic regression, generalized linear models, generalized additive models, linear mixed models, nonlinear models, and decision trees. The procedures provide model selection, dimension reduction, and identification of important variables whenever this is appropriate for the analysis.
In addition to the high-performance statistical procedures described in this book, SAS/STAT includes high-performance utility procedures, which are described in Base SAS Procedures Guide: High-Performance Procedures.