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Clinical SAS Course Syllabus

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This Clinical SAS Course Syllabus curriculum delves into the intricacies of SAS programming and its application in clinical trials. This Clinical SAS Course Syllabus explores everything from SAS Clinical research to Clinical trials. Our Clinical SAS Course Syllabus provides hands-on training to equip you with the skills needed to navigate the complexities of clinical data effectively. The syllabus also now includes topics that are relevant to the current times, so go ahead and enroll in our Clinical SAS Training Institute in Chennai to learn the up-to-date Clinical SAS Course Syllabus. 

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Breakdown of Clinical SAS Course Fee and Batches

Hands On Training
3-5 Real Time Projects
60-100 Practical Assignments
3+ Assessments / Mock Interviews
July 2024
Week days
(Mon-Fri)
Online/Offline

2 Hours Real Time Interactive Technical Training 

1 Hour Aptitude 

1 Hour Communication & Soft Skills

(Suitable for Fresh Jobseekers / Non IT to IT transition)

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July 2024
Week ends
(Sat-Sun)
Online/Offline

4 Hours Real Time Interactive Technical Training

(Suitable for working IT Professionals)

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Syllabus for The Clinical SAS Course

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1

    Working in the SAS Environment

    2

    • 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.
    Creation database from raw data

    3

    • 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.
    Output delivery system

    4

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

    5

    • One-o-one reading
    • One to many
    • Many to many
    • Concatenation
    • Interleaving,
    • Match merge
    Functions

    6

    • Character function
    • Numerical function
    • Arithmetical function
    • Mathematical function
    • Date Function
    Loops in SAS: Do Loops

    7

    • Do Loop
    • Do While
    • Do Until
    Array

    8

    • Definition of array
    • Example of array
    PROCEDURES

    9

    • 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.
    GRAPHS

    10

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

    11

    • 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.
    • Construct sub-queries and in-line views within an SQL procedure step.
    • Compare solving a problem using the SQL procedure versus using traditional SAS programming techniques.
    Macro

    12

    • 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.
    Introduction of SAS and Clinical research

    13

    • 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

    14

    • 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.
    Transform Clinical Trials Data

    15

    • 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.

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