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SAS Short Course

Course Materials Supplemental Materials
Part I: Introduction  

Module 1: Basic introduction to SAS.

            What is SAS?

Module 2: Orientation to SAS

            Using SAS in the Windows environment.

Module 3: SAS Data Handling & file types

            The Data Step

Module 4: Frequently used Procedures (likely to continue into Part II)

            Frequently used PROCs

SAS Institute  SAS Documentation provides documentation for an A - Z list of products.

SAS Base Documentation includes links for Adobe & HTML user guides on SAS Base functions.

What’s new in SAS/STAT software  Introduction to SAS/STAT software

Introduction to: analysis of variance procedures, regression procedures, general linear model estimation, nonparametric analysis, categorical analysis procedures, multivariate procedures, survey sampling and analysis procedures, survival analysis procedures, clustering procedures, structural equation modeling (SEM), statistical modeling with SAS/STAT software, mixed modeling procedures, Bayesian analysis procedures

UCLA Statistical Computing SAS Resources Overview of statistical tests and how to in SAS

NoTSUG (North Texas SAS Users Group).

Recommended text (1): O'Rourke, N., Hatcher, L., & Stepanski, E.J. (2005). A step-by-step approach to using SAS for univariate and multivariate statistics, Second Edition. Cary, NC: SAS Institute Inc.   (All syntax for that book can be found here).

Recommended text (2): Hatcher, L. (1994). A step-by-step approach to using the SAS System for factor analysis and structural equation modeling. Cary, N.C.: SAS Institute Inc.  (All syntax for that book can be found here).

Research and Statistical Support statistical resources workshop

Fairly comprehensive comparison of just about all statistical software packages: Wiki

 

Part II: Intermediate
Module 5: Some basic statistical tests.

            Correlation, Chi-square, and t-tests

Module 6: Mainstream statistical tests

            ANOVA and Linear Regression

Part III: Advanced

Module 7: Component Analysis & Factor Analysis.

            Component and Factor Analysis; and Internal Consistency Analysis

Module 8: Path Analysis & Structural Equation Modeling

            Basic Path Analysis with Manifest Variables

            Some introduction to Structural Equation Modeling (SEM):

                 Stage 1: Verifying the Measurement Model

                 Stage 2: Testing the Structural Model

Module 9: Miscellaneous

            Bootstrapped re-sampling for t-test confidence intervals

            Exploration of Linear Mixed Models (i.e. Hierarchical Linear Modeling).

The DSA SPSS short course
The DSA DIY Introduction to R short course

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Contact Information

Jon Starkweather, PhD

Jonathan.Starkweather@unt.edu

940-565-4066

Richard Herrington, PhD

Richard.Herrington@unt.edu

940-565-2140

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Last updated: 2018.11.06 by Jon Starkweather.

Copyright 2012, 2013, 2014, 2015, 2016, 2017, 2018 by Jonathan D. Starkweather.

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