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Clinical Trial Data Analysis Using Leading Statistical Software

  • 20 weeks
  • 120 Hours

This is the great exposure for Life Science background students to drive into the tech field. Boost your profession to the next level by evolving your technical familiarity with Industry Standard .

Course Overview

Your career in the sought-after position be a Data Scientist in the Health-Care Industry. This course is for those who want to learn how to write Statistical Analysis Software programs and apply in Clinical Research.Software used in this program is to enriched and inspires customers round the world to transfigure data into intelligence. In this program you will get to know the leading Statistical Analysis Software,SQL, Macro and Clinical Training and Project work using CDISC, SDTM, ADaM, TLF.

Advantage

This Clinical Trial Data Analysis Using Leading Statistical Software for Clinical Data Management program will help you to build your career as a Clinical Data Manager and Clinical Trial Progrramer/Researcher/Professional. We design this course by extensive research on job requirement across the world. Completion of this course will make you job ready as Clinical Data Manager. Secure your job in less than 6 months. A comprehensive Program – covering complete knowledges on Statistical Analysis Software, SQL, Macro and Clinical Data Management/ Trial techniques and efficiencies.

What you'll learn

  • Statistical Analysis Software
  • SQL, Macro
  • Clinical Trial Data Analysis

Statistical Analysis Software

  • Components of the Statistical Analysis Software
  • Data-Driven Tasks
  • Turning Data into Information
  • Introducing to Statistical Analysis Software Programs
  • Running Statistical Analysis Software Programs
  • Mastering Fundamental Concepts
  • Diagnosing and Correcting Syntax Errors
  • Statistical Analysis Software Data Libraries
  • Getting Started with the PRINT Procedure
  • Sequencing and Grouping Observations
  • Identifying Observations
  • Special WHERE Statement Operators
  • Customizing Report Appearance
  • Formatting Data Values
  • Creating HTML Reports
  • Reading Raw Data Files: Column Input
  • Reading Raw Data Files: Formatted Input
  • Examining Data Errors
  • Assigning Variable Attributes
  • Changing Variable Attributes
  • Reading Excel Spreadsheets
  • Reading Data Sets and Creating Variables
  • Conditional Processing
  • Dropping and Keeping Variables
  • Reading Excel Spreadsheets Containing Date Fields
  • Concatenating Data Sets
  • Merging Data Sets
  • Combining Data Sets : Additional Features
  • Introduction to Summary Reports
  • Basic Summary Reports
  • The Report Procedure
  • The Tabulate Procedure
  • Producing Bar and pie Chart
  • Enhancing output
  • Producing Plots
  • Overview
  • Review
  • Review of DATA Step Processing
  • Review of Displaying Data Sets
  • Working with Existing Data Sets
  • Outputting Multiple Observations
  • Writing to Multiple Data Sets
  • Selecting Variables and Observations
  • Writing to an External File
  • Creating an Accumulating Total variable
  • Accumulating Totals for a Group of Data
  • Reading Delimited Raw Data Files
  • Controlling When a Record Loads
  • Reading Hierarchical Raw data Files
  • Introduction
  • Manipulating Character values
  • Manipulating Numeric values
  • Manipulating Numeric values based on Dates
  • Converting variable Type
  • Using the PUT Statemen
  • Using the DEBUG Option
  • Do Loop Processing
  • Array Processing
  • Using Arrays
  • Match-merging Two or more Data Sets
  • Simple Joins Using the SQL Procedure
  • Mastering Fundamental Concepts
  • Diagnosing and Correcting Syntax Errors

Advanced Statistical Analysis Software

  • What is SQL?
  • What is the SQL Procedure?
  • Terminology
  • Comparing PROC SQL with the DATA step
  • Note about the Example Table
  • Overview of the select Statement
  • Selecting Columns in a Table
  • Creating New Columns
  • Sorting Data
  • Retrieving rows that satisfy a Condition
  • Summarizing Data
  • Grouping Data
  • Filtering Grouped Data
  • Introduction
  • Selecting Data from More Than One Table by Using joins
  • Using Subqueries to Select Data
  • When to Use Joins and Subqueries
  • Combining Queries with Set Operators
  • Introduction
  • Creating Tables
  • Inserting Rows into Tables
  • >Updating Data Values in a Table
  • Deleting Rows
  • Altering Columns
  • Creating an Index
  • Deleting a Table
  • Using SQL Procedure Tables in Statistical Analysis Software
  • Creating and Using Integrity Constraints in a Table
  • Introduction
  • Using Proc SQL Options to Create and Debug Quires
  • Improving Query Performance
  • Accessing System Information Using DICTIONARY Tables
  • Using Proc SQL with the Macro Facility
  • Formatting PROC SQL output Using the Report Procedure
  • Accessing a DBMS
  • Overview
  • Computing a Weighted Average
  • Comparing Tables
  • Overlaying Missing Data Values
  • Computing Percentages within Subtotals
  • Counting Duplicate Rows in a Table
  • Expanding Hierarchical Data in a Table
  • Summarizing Data in Multiple Columns
  • Creating a Summary Report
  • Creating a Customized Sort Order
  • Conditionally Updating a Table
  • Updating a Table with Values from Another Table
  • Creating and Using Macro Variables
  • Macro Overview
  • Macro Variables
  • Scope of Macro variables
  • Defining Macros
  • Inserting Comments in Macros
  • Macros with Arguments
  • Conditional Macros
  • Macros Repeating PROC Execution
  • Macro Language
  • Macro Processor

Clinical Trial Analysis and Project work using CDISC, SDTM, ADaM, TLF.

  • Introduction to drug development process
  • Drug approval process
  • Introduction about Clinical trials process
  • Introduction of CDISC
  • Why CDISC and DATA standards
  • What are the versions of CDISC
  • Impact of CDISC Standards on Clinical Activities
  • CDISC Models
  • Study Data Tabulation Model (SDTM)
  • Analysis Dataset Models (ADaM)
  • Operational Data Model (ODM)
  • What is SDTM?
  • Observations and Variables in SDTM
  • Special Purpose Datasets
  • General Observation Classes in SDTM
  • SDTM Standard Domain Models
  • DM(Demographics), CO(Comments), SE(Subjects Elements)
  • CM(Concomitant Medication), EX(exposure), SU(Substance Use), EC(Exposure as collected
  • a. AE, MH
  • LB, EG, VS, PE, IE
  • TA, TE, TS, TI and TV
  • Supplemental Qualifies domains and relrec SDTM Annotation on CRF – Concept

Admission Process

Please call to admission counselor for course fees, registration fees, EMI fecilities,registration form and other formalities. Contact to admission counselor
+91-9831765780
+91-9830247087

Who can join?

Any graduate with knowledge of basic computing.

Requirment

1.Personal computer/laptop with webcam and microphone
2.Stable internet connections

Payment details

Bank Details:
KLMS HANDS-ON SYSTEMS PRIVET LIMITED
Account Number: 19700200000420
IFSC Code: BARB0SALTLA (5th letter is numeric zero)
UPI Payment: [email protected]

SAS Clinical Data Management
This Course Include:
  • Live Instructor-Led Course
  • Project and Case Studies
  • Certificate of completion
  • Learn from Experts
  • Placement Assistance
  • Assistance for Global Certification
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