Clinical SAS Programming

Course code : SASPC1

Duration        : 30 Hours

Course Overview

  • Course outline
  • Course objectives
  • An overview of exercises and related files

PART 1 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 (principles of 21 CFR Part 11, International Conference on Harmonization, Good Clinical Practices).
  • Lab exercises

PART 2 Clinical Trials Data Structures

  • Identify the classes of clinical 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.
  • Lab exercises

PART 3 Import and Export Clinical Trials Data

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

PART 4 Transform Clinical 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.
  • Lab exercises

PART 5 Apply Statistical Procedures for Clinical Trials

  • Use SAS procedures to obtain descriptive statistics for clinical trials data (FREQ, UNIVARIATE, MEANS and SUMMARY).
  • Use PROC FREQ to obtain p-values for categorical data .
  • Create output data sets from statistical procedures.
  • Lab exercises

PART 6 Report Clinical Trials Results

  • Use PROC REPORT to produce tables and listings for clinical trials reports.
  • Use ODS and global statements to produce and augment clinical trials reports.
  • Lab exercises

PART 7 Validate Clinical Trial Data Reporting

  • Explain the principles of programming validation in the clinical trial industry.
  • Utilize the log file to validate clinical trial data reporting.
  • Use programming techniques to validate clinical trial data reporting (PROC COMPARE, MSGLEVEL).
  • Identify and Resolve data, syntax and logic errors.
  • Lab exercises

Course Review