Clinical SAS Programming Online Training

Clinical SAS Programming Training is used for clinical data integration, standardizing, organizing and managing clinical research data and metadata. Tysco 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

CLINICAL SAS PROGRAMMING ONLINE TRAINING COURSE CONTENT :

TOPIC 1: ENVIRONMENT & GUIDING PRINCIPLES

  • Clinical SAS Programming Training Overview

TOPIC 2: THE STATISTICAL PROGRAMMERS WORKING ENVIRONMENT

  • Statistical Programmer Work Description
  • Drug/Device Development Process
  • Industry Regulations & Standards
  • Your Clinical Trial Colleagues
  • Guide the  Principles for Statistical Programmer
  • Understand the Clinical SAS Programming Training Study
  • Program a Task Once & Reuse Your Code Everywhere
  • Clinical Trial Data are Dirty
  • Use the SAS Macros Judiciously
  • A Good Programmer Is a Good Student
  • Strive to Make Your Program Readable

TOPIC 3: PREPARING & CLASSIFYING THE CLINICAL TRIAL DATA
TOPIC 4: PREPARING THE CLINICAL TRIAL DATA

  • “Clean” Data If They Are Needed for Analysis
  • Categorize Data If Necessary
  • Avoid the Hardcoding Data

TOPIC 5: CLASSIFYING THE CLINICAL TRIAL DATA

  • Demographics & Trial-Specific Baseline Data
  • Concomitant or Prior Medication Data
  • Medical History Data
  • Investigational the Therapy Drug Log
  • Laboratory Data
  • Adverse Event Data
  • Endpoint/Event Assessment Data
  • Clinical Endpoint Committee Data
  • Study Termination Data
  • Treatment Randomization Data
  • Quality of life Data

TOPIC 6: IMPORTING THE DATA
TOPIC 7: IMPORTING RELATIONAL DATABASES & CLINICAL DATA MANAGEMENT SYSTEMS

  • SAS/ACCESS SQL Pass through Facility
  • SAS/ACCESS LIBNAME Statement

TOPIC 8: IMPORTING THE ASCII TEXT

  • PROC IMPORT & the Import Wizard
  • SAS DATA Step
  • SAS Enterprise Guide

TOPIC 9: IMPORTING THE MICROSOFT OFFICE FILES

  • LIBNAME Statement
  • Import Wizard & PROC IMPORT
  • SAS/ACCESS SQL Pass-Through Facility
  • SAS Enterprise Guide

TOPIC 10: IMPORTING XML

  • XML LIBNAME Engine
  • SAS XML Mapper
  • PROC CDISC

TOPIC 11: IMPORTING FILES IN OTHER PROPRIETARY DATA FORMATS
TOPIC 12: TRANSFORMING DATA & CREATING ANALYSIS DATASETS
TOPIC 13: KEY CONCEPTS FOR CREATING ANALYSIS DATASETS

  • Defining the Variables Once
  • Defining Study Populations
  • Defining Baseline Observations
  • Last Observation Carried Forward
  • Defining the Study Day
  • Windowing Data
  • Transposing Data
  • Categorical Data and Why Zero & Missing Results Differ Greatly
  • Performing Many-to-Many Comparisons/Joins
  • Using Medical Dictionaries
  • Other Tricks & Traps in the Data Manipulation

TOPIC 14: COMMON ANALYSIS DATA SETS

  • Critical Variables Data Set
  • Change from baseline Data Set
  • Time to Event Data Set

TOPIC 15: CREATING TABLES & LISTINGS
TOPIC 16: CREATING TABLES

  • General Approach to Creating Tables
  • A Typical Clinical Trial Table
  • Using the PROC TABULATE to Create Clinical Trial Tables
  • Using the  PROC REPORT to Create Clinical Trial Tables
  • Creating the Continuous/Categorical Summary Tables
  • Creating the Adverse Event Summaries
  • Creating the Concomitant or Prior Medication Tables
  • Creating a Laboratory Shift Table
  • Creating the Kaplan Meier Survival Estimates Tables
TOPIC 17: 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 & Date

TOPIC 18: SAS MACRO BASED REPORTING SYSTEMS

  • Clinical SAS Programming Training Reporting Systems

TOPIC 19: CREATING THE CLINICAL TRIAL GRAPHS
TOPIC 20: COMMON CLINICAL TRIAL GRAPHS

  • Scatter Plot
  • Line Plot
  • Bar Chart
  • Box Plot
  • Odds Ratio Plot
  • Kaplan Meier Survival Estimates Plot

TOPIC 21: SAS TOOLS FOR CREATING THE CLINICAL TRIAL GRAPHS

  • Common Clinical Trial SAS/GRAPH Procedures
  • Using the Annotate Facility for Graph Augmentation

TOPIC 22: SAMPLE GRAPHS

  • Creating a Scatter Plot
  • Creating a Line Plot
  • Creating a Bar Chart
  • Creating a Box Plot
  • Creating an Odds Ratio Plot
  • Creating a Kaplan Meier Survival Estimates Plot

TOPIC 23: OUTPUT OPTIONS

  • Selecting Graphics Drivers
  • Using the ODS Destinations for the  SAS/GRAPH

TOPIC 24: USING THE SAS/GRAPH ASSISTANTS

  • Graph N Go
  • SAS Enterprise Guide
  • ODS Graphics

TOPIC 25: PERFORMING COMMON ANALYSES & OBTAINING STATISTICS
TOPIC 26: OBTAINING DESCRIPTIVE STATISTICS

  • Using the PROC FREQ to Export Descriptive Statistics
  • Using the PROC UNIVARIATE to Export Descriptive Statistics

TOPIC 27: OBTAINING INFERENTIAL STATISTICS FROM CATEGORICAL DATA ANALYSIS

  • Performing a 2×2 Test for Association
  • Perform an NxP Test for Association
  • Perform a Stratified NxP Test for Association
  • Perform Logistic Regression

TOPIC 28: OBTAINING THE INFERENTIAL STATISTICS FROM THE CONTINUOUS DATA ANALYSIS

  • Perform a One sample Test of the Mean
  • Perform a Two sample Test of the Means
  • Perform an N sample Test of the Means

TOPIC 29: OBTAINING TIME-TO-EVENT ANALYSIS STATISTICS
TOPIC 30: OBTAINING CORRELATION COEFFICIENTS
TOPIC 31: GENERAL APPROACH TO THE OBTAINING STATISTICS
TOPIC 32: GENERAL APPROACH TO THE OBTAINING STATISTICS
TOPIC 33: EXPORTING DATA
TOPIC 34: EXPORTING DATA TO FDA

  • Using SAS XPORT Transport Format
  • Creating the  XML Files

TOPIC 35: EXPORTING DATA NOT DESTINED FOR THE FDA

  • Exporting the Data with PROC CPORT
  • Exporting the ASCII Text
  • Exporting the Data to Microsoft Office Files
  • Exporting the Other Proprietary Data Formats

TOPIC 36: ENCRYPTION & FILE TRANSPORT OPTIONS
TOPIC 37: MULTIPLE COMPARISONS AND MULTIPLE ENDPOINTS

  • Introduction
  • Single-Step Tests
  • Closed Testing Methods
  • Fixed-Sequence Testing Methods
  • Resampling-Based Testing Methods
  • Testing Procedures for Multiple Endpoints
  • Gatekeeping Strategies

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