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    • The Simplest Guide to Clinical Trials Data Analysis with SAS

    The Simplest Guide to Clinical Trials Data Analysis with SAS

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    Udemy

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    Mode

    Online

    Fees

    ₹ 2999

    Quick Facts

    particular details
    Medium of instructions English
    Mode of learning Self study
    Mode of Delivery Video and Text Based

    Course and certificate fees

    Fees information
    ₹ 2,999
    certificate availability

    Yes

    certificate providing authority

    Udemy

    The syllabus

    Introduction

    • Course Overview
    • Components of the Pharma/ Life Science Industry
    • Phases of Clinical Trials
    • Data and Reports in Clinical Trials
    • Types of data in Clinical Trials
    • Section Conclusion
    • Clinical Trial Fundamentals

    Get to know the Clinical Study Documents

    • Get to know the Clinical Study Documents - Section Overview
    • Study Documents - The Clinical Study Protocol
    • The Informed Consent
    • The Inclusion- Exclusion Criteria
    • The Statistical Analysis Plan (SAP), mock shells, and Case Report Forms (CRFs)
    • Get to know Clinical Study Documents - Section Conclusion
    • Clinical Study Documents

    Building the Clinical Study Reports (CSR)

    • Building the CSRs - Section Overview
    • SAS OnDemand Registration
    • Logging-in to SAS after registration
    • General SAS Programming Steps for building any CSRs
    • Understanding the Demographics Case Report Form (CRF)
    • Understanding the Demographics Table
    • Planning to program the Demographics Table
    • Importing raw Demographics data into SAS
    • Importing raw data into SAS
    • Building the Demographics table
    • Deciding which PROCs to use
    • Deriving the AGE variable
    • Deriving the AGE variable
    • Obtaining Summary Statistics for AGE
    • Adding the 3rd Treatment Group using Explicit Output
    • Procedures and Variables
    • Deriving the SEX variable
    • Obtaining Summary Statistics for SEX
    • Summarizing Data
    • Concatenating the COUNT and PERCENT variables
    • Deriving the RACE variable
    • Obtaining Summary Statistics for RACE
    • Stacking all 3 Summary Statistics together
    • Fixing the precision points
    • Transposing data
    • Structuring Data
    • Fixing the order of statistical parameters
    • Building the final report
    • Putting the final touches to the report
    • Final Report
    • Building the CSRs - Section Conclusion
    • Final Test

    Final Project

    • Create a Demographics Clinical Study Report

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