Contact No  : +91 8050922145
Skype ID      :  sas.training25
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SAS Training for Clinical Trials (with Project)

SAS is widely used in clinical trial data analysis in pharmaceutical, biotech and clinical research companies. SAS programmers play an important role in clinical trial data analysis. In addition to doctors and clinicians who collect clinical trial data, the group conducting data analysis includes statisticians, clinical data managers (COMs) and SAS programmers. SAS programmers implement the analysis methods on the collected data and provide the study summary tables, data listing and graphs to the statisticians and/or clinicians to write study report. SAS programmers work closely with statisticians and data managers.


Graduate/Post Graduate Degree (B.Tech,MCA,M.Sc,M.S), Pharmacy, Medical Laboratory, Nursing, Biochemistry Microbiology, Biotechnology, MD, MBBS, BHMS, BAMS,MBA.

Training Duration:

50 Days

Mode of Training:

Option 1: Instructor Led online training.
Option 2: Instructor led classroom training.

Take Away:

Soft Copy of Books
Class notes,
Coding for reference,
Assignments for practice
Interview questions,
Resume preparation.

Course Content / Topics:


Introduction of SAS software.
Industries using SAS
Components of SAS System.
Architecture of SAS system.
Functionality of SAS System.
Introduction of SAS windows.

Working in the SAS Environment

Functionality of SAS Windows.
Creating and managing SAS Libraries.
Overview of SAS Data states.
Types of Libraries.
Storing files temporarily and permanently.
Referencing SAS files.

Creating database from raw data

Steps to create a SAS dataset.
Creating SAS dataset using text file.
Creating SAS dataset using text file with delimiters.
Creating SAS dataset using structured text file.
Creating SAS dataset using unstructured text file.
Creating SAS dataset using Excel file.
Creating SAS dataset using Access file.
Creating SAS dataset using values inside the code.

Creating AND Redefining variable

Use with different conditional statements.

Debugging Error Message


Automatic Variables

Use of automatic variables.
Types of automatics variables.
Use of _N_, _ERROR_, _NULL_.
Testing your programs.
Using put statement.
Automatic Variable.

Output delivery system

Concepts of output delivery system. How ODS works and viewing output of ODS in different format. HTML, RTF, PDF etc..

Combination the dataset

One-o-one reading
One to many
Many to many
Match merge


Character function
Numerical function
Arithmetical function
Mathematical function
Date Function

Sampling method

Random sampling

Loops in SAS: Do Loops

Loops are used to iterate through every observation for specified number of times to obtain a desired result

Types of Loops:
        Do Loop
        Do While
        Do Until


Definition of array
Example of array

Procedure in SAS

Procedure Format.
Procedure Contents.
Procedure Options.
Procedure Append.
Procedure Compare.
Procedure Transpose.
Procedure Print.
Procedure Import.
Procedure Export.
Procedure Datasets.
Procedure Tabulate.
Procedure Chart, Gchart, Gplot.
Procedure Report.


Introduction to graphics.
Introduction to graphics.
Types of Graphics (with latest models)
Defining procedure Graphics.

Advance SAS Topics

Proc SQL

Generate detail reports by working with a single table, joining tables, or using set operators in the SQL procedure.
Generate summary reports by working with a single table, joining tables, or using set operators in the SQL procedure.
Compare solving a problem using the SQL procedure versus using traditional SAS programming techniques.


Create and use user-defined and automatic macro variables within the SAS Macro Language.
Automate programs by defining and calling macros using the SAS Macro Language.
Understand the use of macro functions.

Introduction of SAS and Clinical research

SAS role in Clinical Research.
What is Clinical trial?
What is Protocol and role of Protocol in Clinical Research?
Which is playing main role in Clinical Research?

Clinical Trials Data Structures

Identify the classes of clinical trials data (demographic, lab, baseline, concomitant medication, etc.).
Identify key CDISC principals and terms.
Describe the structure and purpose of the CDISC SDTM data model.
Describe the structure and purpose of the CDISC ADaM data model.
Describe the contents and purpose of define.xml.

Statistic and Report Clinical Trials Results

Use SAS procedures to obtain descriptive statistics for clinical trials data (FREQ, UNIVARIATE, MEANS, SUMMARY).
Use PROC FREQ to obtain p-values for categorical data (22 and NxP test for association).
Use PROC TTEST to obtain p-values for continuous data (one-sample, paired and two-sample t-tests).
Create output data sets from statistical procedures.
Using ODS with PROC REPORT and PROC TABULATE to generate nice looking tables and listings
Producing Bar and Pie charts using PROC GPLOT and PROC GCHART

Transform Clinical Trials Data

Apply categorization and windowing techniques to clinical trials data.
Transpose SAS data sets.
Apply 'observation carry forward' techniques to clinical trials data (LOCF, BOCF, WOCF).
Calculate 'change from baseline' results.

Clinical Project

Project 1
Project 2
Project 3