Welcome to Statistics and Operations Research

SAS has long developed software for data analysis, econometrics, operations research, and quality improvement. The purpose of these pages is to provide our users with technical information about using this software, including details about software capabilities, examples, papers, e-newsletter, and communities.

Featured News

SGF SGF 2019

The following tutorials by R&D staff are on tap for SAS Global Forum 2019:

  • Introduction to Logistic Regression
  • Survey of Missing Data Analysis Using SAS
  • Advanced Methods for Survival Analysis Using SAS
  • Causal Analysis with Observational Data: Methods and Applications
  • Quantile Regression in Practice
  • Introduction to Modern Machine Learning Techniques in SAS Visual Data Mining and Machine Learning

Super demos from SAS employees will be presented all three days the Quad is open. Click here to see a complete schedule.

SAS Econometrics 8.2: HMM Procedure

The HMM procedure supports hidden Markov models, which have been widely applied in economics, finance, science, and engineering. Hidden Markov models have many well-known aliases, such as general state space models, regime-switching models, Markov-switching models, and Markov regime-switching models. This procedure supports Gaussian hidden Markov models.

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Power Analysis for Generalized Linear Models Using the New CUSTOM Statement in PROC POWER

The CUSTOM statement that was added to the POWER procedure in SAS/STAT 14.2 expands the scope of supported data analyses to include generalized linear models and other extensions of existing capabilities. It works in concert with an exemplary data set and the SAS/STAT procedure that you plan to use for the eventual data analysis. This paper explains the method and demonstrates it for a variety of data analyses, including Poisson regression, logistic regression, and zero-inflated models.

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tech support tip Compute Estimates and Tests of Agreement among Multiple Raters Compute estimates and tests of agreement among multiple raters when responses (ratings) are on a nominal or ordinal scale. For a nominal or ordinal response, kappa statistics can be computed. For a numerically-coded, ordinal response, Kendall's coefficient of concordance can be computed.

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