The Simplest Guide to Clinical Trials Data Analysis with SAS
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The Simplest Guide to Clinical Trials Data Analysis with SAS at UDEMY Overview
Duration | 2 hours |
Mode of learning | Online |
Credential | Certificate |
The Simplest Guide to Clinical Trials Data Analysis with SAS at UDEMY Highlights
- Enroll to this course by Great Learning for free
- Learn essential concepts needed to work in the Pharma industry in the areas of Biostatistics and Clinical Data Management
The Simplest Guide to Clinical Trials Data Analysis with SAS at UDEMY Course details
- This course gives an introduction to the Pharmaceutical/ Life Science industry in a simple and visual style that is easy to understand. It shows how SAS is used as a tool to work with the vast amount of clinical data within this industry
- The course takes you through an example clinical study sample data, and generate various Clinical Study Reports that are submitted to the FDA (in the US) or other regulatory authorities in other countries
- You will not only hone your SAS programming skills but will also learn essential concepts needed to work in the Pharma industry in the areas of Biostatistics and Clinical Data Management.
The Simplest Guide to Clinical Trials Data Analysis with SAS at UDEMY Curriculum
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
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
Building the Clinical Study Reports (CSR)
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
Deciding which PROCs to use
Deriving the AGE variable
Obtaining Summary Statistics for AGE
Adding the 3rd Treatment Group using Explicit Output
Deriving the SEX variable
Obtaining Summary Statistics for SEX
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
Fixing the order of statistical parameters
Building the final report
Putting the final touches to the report
Building the CSRs - Section Conclusion
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