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1. |  SAS/STAT 9.2 User's Guide: Statistical Graphics Using ODS (Book Excerpt) By: Publisher: SAS Publishing Publication Date: 11-MAR-2008 Insert Date: 16-SEP-2009 Bookshelf Slots: 1.0 | Overview: SAS/STAT 9.2 User's Guide: Statistical Graphics Using ODS (Book Excerpt)
Describes usage of the Output Delivery System for statistical graphics in SAS/STAT 9.2.
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2. |  SAS/STAT 9.2 User's Guide: The GLIMMIX Procedure (Book Excerpt) By: Publisher: SAS Publishing Publication Date: 11-MAR-2008 Insert Date: 15-JUN-2009 Bookshelf Slots: 1.0 | Overview: SAS/STAT 9.2 User's Guide: The GLIMMIX Procedure (Book Excerpt)
The GLIMMIX procedure fits and analyzes generalized linear mixed models (GLMM), models with random effects for data that can be nonnormally distributed.
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3. |  SAS/STAT 9.2 User's Guide: The REG Procedure (Book Excerpt) By: Publisher: SAS Publishing Publication Date: 11-MAR-2008 Insert Date: 11-JUN-2009 Bookshelf Slots: 1.0 | Overview: SAS/STAT 9.2 User's Guide: The REG Procedure (Book Excerpt)
The REG procedure is a general-purpose procedure for linear regression.
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4. |  SAS/STAT 9.2 User's Guide: The PHREG Procedure (Book Excerpt) By: Publisher: SAS Publishing Publication Date: 11-MAR-2008 Insert Date: 11-JUN-2009 Bookshelf Slots: 1.0 | Overview: SAS/STAT 9.2 User's Guide: The PHREG Procedure (Book Excerpt)
The PHREG procedure performs regression analysis of survival data based on the Cox proportional hazards model and its extensions.
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5. |  SAS/STAT 9.2 User's Guide: The MIXED Procedure (Book Excerpt) By: Publisher: SAS Publishing Publication Date: 11-MAR-2008 Insert Date: 11-JUN-2009 Bookshelf Slots: 1.0 | Overview: SAS/STAT 9.2 User's Guide: The MIXED Procedure (Book Excerpt)
The MIXED procedure fits a variety of mixed linear models to data and enables you to use these fitted models to make statistical inferences about the data.
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6. |  SAS/STAT 9.2 User's Guide: The LOGISTIC Procedure (Book Excerpt) By: Publisher: SAS Publishing Publication Date: 11-MAR-2008 Insert Date: 11-JUN-2009 Bookshelf Slots: 1.0 | Overview: SAS/STAT 9.2 User's Guide: The LOGISTIC Procedure (Book Excerpt)
The LOGISTIC procedure fits linear logistic regression models for discrete response data by the method of maximum likelihood. It can also perform conditional logistic regression for binary response data and exact conditional logistic regression for binary and nominal response data.
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7. |  SAS/STAT 9.2 User's Guide: The GLM Procedure (Book Excerpt) By: Publisher: SAS Publishing Publication Date: 11-MAR-2008 Insert Date: 11-JUN-2009 Bookshelf Slots: 1.0 | Overview: SAS/STAT 9.2 User's Guide: The GLM Procedure (Book Excerpt)
The GLM procedure uses the method of least squares to fit general linear models. Among the statistical methods available in PROC GLM are regression, analysis of variance, analysis of covariance, multivariate analysis of variance, and partial correlation.
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8. |  SAS/STAT 9.2 User's Guide: The GENMOD Procedure (Book Excerpt) By: Publisher: SAS Publishing Publication Date: 11-MAR-2008 Insert Date: 11-JUN-2009 Bookshelf Slots: 1.0 | Overview: SAS/STAT 9.2 User's Guide: The GENMOD Procedure (Book Excerpt)
The GENMOD procedure fits generalized linear models.
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9. |  SAS/STAT 9.2 User's Guide: The FREQ Procedure (Book Excerpt) By: Publisher: SAS Publishing Publication Date: 11-MAR-2008 Insert Date: 11-JUN-2009 Bookshelf Slots: 1.0 | Overview: SAS/STAT 9.2 User's Guide: The FREQ Procedure (Book Excerpt)
The FREQ procedure produces one-way to n-way frequency and contingency (crosstabulation) tables. For two-way tables, PROC FREQ computes tests and measures of association. For n-way tables, PROC FREQ provides stratified analysis by computing statistics across, as well as within, strata.
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10. |  Data Preparation for Analytics Using SAS® By: Gerhard Svolba Publisher: SAS Publishing Publication Date: 01-NOV-2006 Insert Date: 07-JUN-2009 Bookshelf Slots: 1.0 | Overview: Data Preparation for Analytics Using SAS®
Written for anyone involved in the data preparation process for analytics, Gerhard Svolba's Data Preparation for Analytics Using SAS offers practical advice in the form of SAS coding tips and tricks, and provides the reader with a conceptual background on data structures and considerations from a business point of view. The tasks addressed include viewing analytic data preparation in the context of its business environment, identifying the specifics of predictive modeling for data mart creation, understanding the concepts and considerations of data preparation for time series analysis,...
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