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Clinical SAS Training Program | Clinformatiq
SAS

Clinical SAS Training Program

Base SAS • Advanced SAS • Clinical Programming • CDISC SDTM/ADaM • TLFs

Become a Clinical SAS Programmer — from fundamentals to TLFs

This practitioner-focused program covers Base SAS, data management, macros, PROC SQL, ODS reporting, clinical programming workflows, CDISC SDTM/ADaM implementation and generation of tables, listings and figures used in clinical study reports.

Duration: 60 Days
Mode: Online / Classroom
Level: Beginner → Advanced
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Program Curriculum

Module 1: Getting Started with SAS

  • SAS Installation and Access
  • SAS Programming Steps (Nuts and Bolts)
  • DATA Step Statements & SAS Input Statements
  • Key Data Warehouse Concepts
  • Execution of SAS Programs (Compile & Execution)

Module 2: Overview of SAS Environment

  • SAS Comments
  • SAS Dataset Definition & Data Types
  • Two Parts of a SAS Program
  • Difference between DATA and PROC Steps
  • Navigating the SAS Windows Environment (Editor, Log, Output, Explorer, Results)
  • Submitting a SAS Program
  • Reading SAS Log and Output Window
  • Referencing Files & Folders in SAS
  • SAS Libraries (Permanent & Temporary)
  • SAS Datasets with SAS Explorer
  • SAS Products / Modules
  • SAS in Different Sectors
  • SAS System Options & Global Statements

Module 3: SAS Base – Data Access

  • Creating SAS Programs (Saving, Editing, Opening)
  • Creating SAS Datasets from Raw Data
  • Referencing a SAS Library (Temporary & Permanent)
  • Informats & Formats (Including User-Defined Formats)
  • Methods of Data Input into SAS: View Table, Internal & External Raw Data, INFILE
  • Import Wizard & PROC IMPORT
  • Program Testing
  • Assignments + Solutions + Key Takeaways

Module 4: Data Management

  • Reading Data from One Dataset to Another
  • Sub-setting Data
  • Creating & Modifying Variables
  • SAS Dataset Statements & Options
  • Merge Concepts

Module 5: Conditional Statements & Loops

  • IF Statement & Nested IF
  • DO Loop, DO WHILE, DO UNTIL
  • Arrays in SAS
  • Assignments + Solutions + Key Takeaways

Module 6: SAS Functions

  • Character Functions
  • Numeric Functions
  • Date Functions
  • Time Functions
  • Changing Variable Types

Module 7: Utility SAS Procedures

  • PROC CONTENTS, PROC PRINT, PROC APPEND, PROC SORT
  • PROC FORMAT, PROC COMPARE, PROC TRANSPOSE, PROC RANK
  • PROC COPY, PROC CATALOG, PROC CPORT, PROC CIMPORT
  • PROC DATASETS, PROC SETINIT
  • Assignments + Solutions + Key Takeaways

Module 8: SAS/STAT for Analysis

  • PROC FREQ
  • PROC TRANSPOSE
  • PROC STANDARD
  • PROC UNIVARIATE
  • PROC MEANS / SUMMARY
  • PROC CORR
  • PROC REG

Module 9: SAS ODS – Data Presentation

  • ODS Concepts
  • SAS Output in Different Formats: RTF, HTML, PDF, XML, MS-Office

Module 10: Reporting Procedures

  • PROC PRINT, PROC TABULATE, PROC REPORT, PROC EXPORT
  • Custom Reporting
  • Using NULL Dataset
  • PUT & FILE Statements for Customization
  • Assignments + Solutions + Key Takeaways

Module 11: SAS Graphs & Plot Procedures

  • PROC PLOT, PROC GPLOT, PROC CHART, PROC GCHART
  • PROC G3D, PROC SGPLOT, PROC GBARLINE

Module 12: Advanced SAS – SQL

  • SQL Introduction, Terminology, and Statements
  • PROC SQL in SAS
  • Creating & Deleting Tables
  • SELECT, WHERE, ORDER BY, GROUP BY Clauses
  • SQL Joins & Views
  • CASE Operator
  • Assignments + Solutions + Key Takeaways

Module 13: Advanced SAS – Macros

  • Introduction & Uses of Macros
  • Macro Processor & Components
  • Automatic & User-Defined Macros
  • Macro Variables (Local & Global)
  • %LET, %DO, %LOCAL, %GLOBAL, %MACRO Statements
  • CALL SYMPUT in DATA Step
  • Macro Parameters (Positional, Keyword, Mixed)
  • Macro Functions & Conditions (%IF / %THEN)
  • Invoking Macros
  • Debugging Macro Errors (MPRINT, MLOGIC, SYMBOLGEN)
  • Assignments + Solutions + Key Takeaways

Module 14: Additional SAS Concepts

  • SAS Coding Standards
  • Efficient SAS Programming
  • Error Handling Concepts

Module 15: SAS in Clinical Programming

  • Role of SAS in Clinical Research
  • Clinical Trials Overview
  • Clinical Trials Data Structures (Demographic, Lab, Baseline, etc.)
  • CDISC Principles & Terminology

Module 16: CDISC – SDTM Data Model

  • SDTM Overview, Purpose, Domains, Variables & Role Concept
  • General Observation Classes
  • Controlled Terminology
  • SDTM Mapping Process
  • Design & Implementation in SAS

Module 17: CDISC – ADaM Data Model

  • ADaM Overview & Principles
  • Traceability & Workflow
  • ADaM Process, Data & Metadata
  • Variable Metadata & Value-Level Metadata
  • Controlled Terminology / Code Lists
  • Core Variables & ADSL Dataset
  • ADaM Standard Implementation

Module 18: Basic Statistics for Clinical SAS

  • Data Exploration & Preparation
  • Summary Statistics – Central Tendency
  • Descriptive Statistics (Samples & Populations)
  • Hypothesis Testing (Chi-square, ANOVA)

Module 19: Statistical Analysis & Reporting in Clinical Trials (TLFs)

  • Using SAS Procedures (FREQ, UNIVARIATE, MEANS, SUMMARY)
  • Creating Output Datasets from Statistical Procedures
  • Bar & Pie Charts (PROC GPLOT, PROC GCHART)
  • Customized Clinical Trial Tables, Listings & Figures
  • PROC REPORT for TLFs
  • Using ODS with PROC REPORT to Generate TLFs
  • SAS XPORT Transport Format
  • Key Clinical Documents (Mock Shells, SAP, Protocol, Specification File)

Tools & Software Covered

  • SAS Base and SAS/STAT
  • ODS and Output Formats (RTF, PDF, HTML, XPT)
  • PROC SQL and PROC REPORT
  • Excel for data review and reconciliation
  • Optional overview: Unix/Linux commands for clinical environment
  • CDISC tools (SDTM/ADaM mapping templates & validators)

Program Benefits & Learning Outcomes

Practical Skillset

Hands-on coding, data manipulation, reporting and real clinical dataset practice.

Clinical Relevance

Learn CDISC standards and produce TLFs aligned with clinical study reporting needs.

Placement Support

Resume and interview prep, sample mock shells and placement guidance for clinical programming roles.

What You Will Learn

  1. Core SAS programming and data management techniques for clinical data.
  2. Advanced macro programming and reusable code design.
  3. PROC SQL and reporting with PROC REPORT & ODS.
  4. Implement SDTM & ADaM mapping and create ADaM datasets (ADSL, BDS, etc.).
  5. Generate tables, listings and figures used in clinical study reports.
  6. Prepare XPT transport files and key clinical documents like mock shells and SAP-aligned specifications.

Assessments & Capstone Project

  • Module-wise quizzes, coding assignments and solution walkthroughs.
  • Midterm practical assessment focusing on data management & PROC SQL.
  • Final capstone: end-to-end clinical programming project — SDTM mapping, ADaM creation and TLF generation with mock shell.

Career Pathways & Job Roles

After completing this program, students are prepared for roles including:

  • Clinical SAS Programmer (Jr/Sr)
  • Statistical Programmers
  • SDTM / ADaM Implementation Specialist
  • Biostatistics Data Programmer
  • TLF Developer / Clinical Reporting Analyst
  • Clinical Data Analyst
Employers

Pharmaceutical companies, CROs, biotech firms and research institutes.

Career Growth

Progress from junior programmer → senior programmer → lead/manager → statistical programming manager.

Salary Outlook

Competitive salaries that increase significantly with CDISC and clinical experience.

Frequently Asked Questions

Do I need prior programming experience?

No. The program starts with fundamentals and builds up to advanced clinical programming topics with hands-on practice.

Will I get hands-on datasets?

Yes — students work with sample clinical datasets, SDTM mapping templates and ADaM examples in lab sessions.

Is certification included?

We provide guidance for industry certifications and help prepare portfolio-ready projects that support interviews.

Ready to become a Clinical SAS Programmer?

Enroll now for practical training, mentorship and placement support to start your clinical programming career.

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