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
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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
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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).
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