This purpose of this presentation is to show you how SAS Enterprise Guide (EG) for Windows can be used for all your teaching and research needs -- whether you are an experienced SAS user or have never used SAS before. EG is a thin client interface to the SAS System that provides you transparent access to data, point-and-click usability, a customizable user interface, and easy export of your results to other software applications.
Will Not Attend
Version 9 of SAS/STAT software brings you a variety of new tools for your statistical computing needs. The Power and Sample Size Application (PSS) provides sample size and power computations for a variety of analyses through a web interface. Experimental software in Version 9 moves SAS/STAT in new directions, including robust regression, which is supported by the ROBUSTREG procedure, and logistic regression for sample survey data, available with the SURVEYLOGISTIC procedure. In response to user requests, a number of procedures have been enhanced significantly. Conditional logistic regression is available in the LOGISTIC procedure through the new STRATA statement, and scoring of data sets is available through the new SCORE statement.
SAS and ESRI have a strategic, corporate relationship which can enhance the use of GIS and analytic intelligence both within and across departments. This purpose of this presentation is to introduce the SAS Bridge to ESRI, describe how it can be used in Higher Education, and illustrate this capability integration with a demonstration.
Session 4 is full. You will be placed on a waiting list if you register for this Session.
Session 5 is full. You will be placed on a waiting list if you register for this Session.
This presentation will take researchers familiar with the general linear model and SAS PROC GLM and introduce them to the linear mixed model and SAS PROC MIXED. We will cover random effects models in both balanced and unbalanced data situations, comparing results you would get from GLM to the results from MIXED. A brief introduction to repeated measures models will be presented, as well as a section on common problems in the use of PROC MIXED.
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