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Clinical SAS Programming Training

Clinical SAS Programming Training Introduction:

Clinical SAS Programming Training is used for clinical data integration, standardizing, organizing and managing clinical research data and metadata.Global Online Trainings offers online Clinical SAS Programming Online Training for supporting all its participants in achieving promptness and competence by mechanizing repeatable clinical data integration projects.This is a new product offering from SAS that focuses on pharmaceutical industry needs for managing, verifying and transforming the creation of industry mandated data standards such as the Clinical Data Interchange Standards Consortium.This project is coordinated by best subject matter experts and SAS Clinical online course  tutorials



TOPIC 1: Environment and Guiding Principles
  • The Statistical Programmer’s Working Environment
  • Statistical Programmer Work Description
  • The Drug/Device Development Process
  • Industry Regulations and Standards
  • A Good Programmer Is a Good Student
  • Strive to Make Your Programming Readable
TOPIC 3: Introduction to SAS and Data manipulation
  • Introduction to SAS (Background & History)
  • Different SAS windows
  • Creation of library,
  • Data entry, Rules /attributes of variables, Different formats
  • SAS statements: Keep, Drop, Rename, label, length, if condition, If-then- else     condition, if-then-delete condition, Where condition
  • SAS functions: Input, Put, Compress, compbl, Substring , Concatenate, Scan, upcase,  lowcase, propcase, left, right, strip, trim, count/n, nmiss, mean, std, min, max, median,put,input etc..
  • SAS procedures: Proc sort, Proc transpose, Proc copy, Proc append, Dataset Merging
TOPIC 5: Demographics and Trial-Specific Baseline Data
  • Concomitant or Prior Medication Data
  • Medical History Data
  • Investigational Therapy Drug Log
  • Laboratory Data
  • Adverse Event Data
TOPIC 7: Importing ASCII Text
  • PROC IMPORT and the Import Wizard
  • SAS DATA Step
  • SAS Enterprise Guide
TOPIC 9: Importing XML
  • XML LIBNAME Engine
  • SAS XML Mapper
  • Importing Files in Other Proprietary Data Formats


TOPIC 11: Defining Study Day
  • Windowing Data
  • Transposing Data
  • Categorical Data and Why Zero and Missing Results Differ Greatly
  • Performing Many-to-Many Comparisons/Joins
  • Using Medical Dictionaries
  • Other Tricks and Traps in Data Manipulation
TOPIC 13: Creating Tables
  • General Approach to Creating Tables
  • A Typical Clinical Trial Table
TOPIC 15: Creating Clinical Trial Graphs
  • Kaplan-Meier Survival Estimates Plot
  • Histogram
  • Normality plot
  • Line graph,
  • Pie chart
TOPIC 17: Performing an NxP Test for Association
  • Performing a Stratified NxP Test for Association
  • Performing Logistic Regression
  • Obtaining Inferential Statistics from Continuous Data Analysis
  • Performing a One-Sample Test of the Mean
  • Performing a Two-Sample Test of the Means
  • Performing an N-Sample Test of the Means
  • Exporting Data to the FDA
  • Using the SAS XPORT Transport Format
  • Creating XML Files
TOPIC 2: Your Clinical Trial Colleagues
  • Guiding Principles for the Statistical Programmer
  • Understand the Clinical Study
  • Program a Task Once and Reuse Your Code Everywhere
  • Clinical Trial Data Are Dirty
  • Use SAS Macros Judiciously
TOPIC 4: Preparing and Classifying Clinical Trial Data
  • Preparing Clinical Trial Data
  • Clean” the Data If They Are Needed for Analysis
  • Categorize Data If Necessary
  • Avoid Hardcoding Data
  • Classifying Clinical Trial Data
TOPIC 6: Importing Data
  • Importing Relational Databases and Clinical Data Management Systems
  • SAS/ACCESS SQL Pass-Through Facility
TOPIC 8: Importing Microsoft Office Files
  • LIBNAME Statement
  • Import Wizard and PROC IMPORT
  • SAS/ACCESS SQL Pass-Through Facility
  • SAS Enterprise Guide
TOPIC 10: Key Concepts for Creating Analysis Data Sets
  • Defining Variables Once
  • Defining Study Populations
  • Defining Baseline Observations
  • Last Observation Carried Forward (LOCF)
TOPIC 12: Common Analysis Data Sets
  • Critical Variables Data Set
  • Change-from-Baseline Data Set
  • Time-to-Event Data Set
TOPIC 14: Creating Listings : Output Appearance Options and Issues
  • Creating ASCII Text Output
  • Creating Rich Text Format (RTF) Output
  • Creating Portable Document Format (PDF) Files
  • Page X of N Pagination Solutions
  • Footnote Indicating SAS Program and Date
  • SAS Macro-Based Reporting Systems
TOPIC 16: Performing Common Analyses and Obtaining Statistics
  • Obtaining Descriptive Statistics
  • Using PROC FREQ to Export Descriptive Statistics
  • Using PROC UNIVARIATE to Export Descriptive Statistics
  • Obtaining Inferential Statistics from Categorical Data Analysis
  • Performing a 2×2 Test for Association
  • Using PROC TABULATE to Create Clinical Trial Tables
  • Using PROC REPORT to Create Clinical Trial Tables
  • Creating Continuous/Categorical Summary Tables
  • Creating Adverse Event Summaries
  • Creating Concomitant or Prior Medication Tables
  • Creating a Laboratory Shift Table
  • Creating Kaplan-Meier Survival Estimates Tables
TOPIC 18: Exporting Data Not Destined for the FDA
  • Exporting Data with PROC CPORT
  • Exporting ASCII Text
  • Exporting Data to Microsoft Office Files
  • Exporting Other Proprietary Data Formats
  • Encryption and File Transport Options

Clinical SAS Programming Training Prerequisites:

  • Knowledge of Base SAS
  • Deep understanding of clinical programming concepts
  • Basic understanding of statistics

Clinical SAS Programming Training Curriculum:

Clinical Trials Process

Describe the clinical research process (phases, key roles, key organizations), Interpret a Statistical Analysis Plan, Derive programming requirements from an SAP and an annotated Case Report Form, Describe regulatory requirements 

Clinical Trials Data Structures

SAS Clinical online course  gives Identify the classes of Clinical SAS Programming Training 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.

Import and Export Clinical Trials Data

Apply regulatory requirements to exported SAS data sets (SAS V5 requirements).

Manage Clinical Trials Data

SAS Clinical online course has Access DICTIONARY Tables using the SQL procedure., Examine and explore clinical trials input data (find outliers, missing vs. zero values, etc).

Transform Clinical SAS Programming Training 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, Obtain counts of events in clinical trials.

Apply Statistical Procedures for Clinical Trials

Use SAS procedures to obtain descriptive statistics for Clinical SAS Programming Training trials data (FREQ, UNIVARIATE, MEANS, SUMMARY). Use PROC FREQ to obtain p-values for categorical data (2×2 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.

Macro Programming for Clinical Trials

Create and use user-defined and automatic macro variables., SAS Clinical online course has Automate programs by defining and calling macros, Use system options to debug macros and display values of macro variables in the SAS log (MPRINT, SYMBOLGEN, MLOGIC, MACROGEN).

Report Clinical SAS Programming Training Trials Results

Use PROC REPORT to produce tables and listings for Clinical SAS Programming Training trials reports., Use ODS and global statements to produce and augment clinical trials reports.

Validate Clinical SAS Programming Training Trial Data Reporting

Explain the principles of programming SAS Clinical online course  validation in the Clinical SAS Programming Training trial industry, Utilize the log file to validate clinical trial data reporting., Use programming techniques to validate Clinical SAS Programming Training trial data reporting , Identify and Resolve data, syntax and logic errors.


By the end of Clinical SAS Programming Training you will exhibit the following capabilities:

  • Illustrate the fundamental knowledge of Clinical SAS Programming Training trial designs, alternative trial designs and statistical analysis
  • Access, manage, and transform clinical trials data
  • Create tables, listings, and clinical trial graphs
  • Use PROC REQ and PROC UNIVARIATE to export descriptive statistics
  • Work on the analysis of stratified data
  • Interpret various methods used for multiple comparisons and multiple endpoints
  • Decide reference intervals for safety and diagnostic measures
  • Evaluate results from incomplete data
Target audience:
  • Life Science or Bioinformatics graduates
  • SAS programmer
  • Clinical Programmer

How SAS Works :

  • Writing Your First SAS Program
  • A Simple Program To Read Raw Data And Produce A Report
  • Enhancing The Program
  • More On Comment Statements
  • Internal Processing In SAS
  • How SAS Works
  • The Compilation Phase
  • The Execution Phase
  • Processing A Data Step: A Walkthrough
  • Creating The Input Buffer And The Program Data Vector
  • Writing An Observation To The SAS Data Set
  • Four Types Of SAS Libraries
  • SAS Libraries
  • Work Library
  • SAS help Library
  • SAS user Library

Reading Raw Data Into SAS :

  • What Is Raw Data?
  • Definitions
  • Data Values
  • Numeric Value
  • Character Value
  • Standard Data
  • Nonstandard Data
  • Numeric Data
  • Character Data
  • Choosing An Input Style
  • List Input
  • Modified List Input
  • Column Input
  • Formatted Input
  • Named Input
  • Instream Data
  • Creating Multiple Records From Single Input Row
  • Reading Data From External Files
  • Reading Blank Separated Values (List Or Free Form Data):
  • Reading Raw Data Separated By Commas (.Csv Files):
  • Reading In Raw Data Separated By Tabs (.Txt Files):
  • Using Informats With List Input
  • Supplying An Informat Statement With List Input
  • Using List Input With Embedded Delimiters
  • Reading Raw Data That Are Aligned In Columns:
  • Method 1: Column Input
  • Method 2: Formatted Input
  • Using More Than One Input Statement: The Single Trailing 
  • Reading Column Data That Is On More Than One Line
  • Mixed-Style Input:
  • Infile Options For Special Situations
  • Flowover
  • Missover
  • Truncover
  • Pad
  • Using Lrecl To Read Very Long Lines Of Raw Data
  • Checking Your Data After It Has Been Read Into SAS
  • Reading Data From A Data set