OBJECTIVES: This course is designed for experienced SAS users to enhance participants' knowledge in using SAS as a senior analyst / Biostatistician position.
TOPICS: The course will introduce you SAS MACRO, SAS SQL, combining multiple datasets, using SAS to do reports and applying SAS programming in statistics which includes Regression with SAS, LOGISTIC Regression with SAS, T-test, ANOVA, and other major popular statistical methods.
GOAL: Upon the completion of this course, you will be able to interpret the SAS outputs, provide your suggestions on how to do the models, troubleshooting, mentoring junior SAS programmers, and successfully pass SAS advanced Programming certification exam.
1. Overview of Multiple Datasets
Concatenating data set using SET statement
Interleaving several datasets
Merging datasets: one-to-one matching
Merging datasets: simple match
Updating data
2. Generating Reports
Generating list reports using the PRINT procedure
Generating frequency tables using PROC FREQ procedure
Generating report using MEANS procedure
Generating report using REPORT procedure and options
Enhancing report through the use of labels, SAS formats, titles, footnotes and SAS System reporting options
Generation report using TABULATE procedure
3. Data Cleaning Techniques and Troubleshooting
Syntax errors-missing semicolon
Identifying and resolve programming logic errors
Identifying data errors such as invalid data and missing values
Identifying invalid values for categorical variables using PROC FREQ
Identifying extreme values or outliers using PROC UNIVARITE
4. Introduction to SQL
Overview of SQL
PROC SQL syntax
PROC SQL statements
PROC SQL examples
5. Introduction to Macro in SAS
Getting Started with the Macro Facility
Macro Variables
Creating and running a macro program
Commonly encountered problems
SAS System options for debugging macros
Macro function
6. Common Statistical Procedures Using SAS System
Introduction
Recoding Data
Two-way Frequency Tables
Computing Chi-square from Frequency Counts
Logistic Regression with SAS
T-test: testing differences between two means
Analysis of variance: two independent variables
Generalized Linear Models
Poisson Regression
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