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SAS Global Certification program


Programmer/Analyst

SAS Certified Clinical Trials Programmer Using SAS 9

Validates a candidates' ability to apply SAS programming skills to clinical trials data

Successful candidates should have experience in
  • clinical trials process
  • accessing, managing, and transforming clinical trials data
  • statistical procedures and macro programming
  • reporting clinical trials results
  • validating clinical trial data reporting.
There are two methods available to earn this credential:
  • pass the Clinical Trials Programming Using SAS 9 exam
or if you currently hold the SAS Certified Base Programmer for SAS 9 credential:
  • pass the Clinical Trials Programming Using SAS 9 – Accelerated Version exam
Select an exam to see the full content for each:

Clinical Trials Programming Using SAS 9
Clinical Trials Programming Using SAS 9 – Accelerated Version

Required Exam

Candidates who earn this credential will have earned a passing score on the Clinical Trials Programming Using SAS 9 exam. This exam is administered by SAS and Pearson VUE.
  • 99 multiple-choice and short-answer questions (must achieve score of 70% correct to pass)
  • 3 hours to complete exam
  • Use exam ID A00-280; required when registering with Pearson VUE.
Exam topics include:
The following exam objectives are subject to change during the development process and will be updated prior to exam registration.

  • 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).
  • 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.
    • Describe the contents and purpose of define.xml.
  • Import and Export Clinical Trials Data
    • Combine SAS data sets.
    • Efficiently import and subset SAS data sets.
    • Access data in an Excel workbook (LIBNAME and PROC IMPORT/EXPORT).
    • Create temporary and permanent SAS data sets.
    • Apply regulatory requirements to exported SAS data sets (SAS V5 requirements).
  • Manage Clinical Trials Data
    • Investigate SAS data libraries using base SAS utility procedures (PRINT, CONTENTS, FREQ).
    • Access DICTIONARY Tables using the SQL procedure.
    • Sort observations in a SAS data set.
    • Create and modify variable attributes using options and statements in the DATA step.
    • Examine and explore clinical trials input data (find outliers, missing vs. zero values, etc).
  • Transform Clinical Trials Data
    • Process data using DO LOOPS.
    • Process data using SAS arrays.
    • Retain variables across observations.
    • Use assignment statements in the DATA step.
    • Apply categorization and windowing techniques to clinical trials data.
    • Use SAS functions to convert character data to numeric and vice versa.
    • Use SAS functions to manipulate character data, numeric data, and SAS date values.
    • 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 trials data (FREQ, UNIVARIATE, MEANS, SUMMARY).
    • Use PROC FREQ to obtain p-values for categorical data (2x2 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.
    • 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 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.
  • 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.

Required Exam

Candidates who earn this credential will have earned a passing score on the Clinical Trials Programming Using SAS 9 exam. This exam is administered by SAS and Pearson VUE.
  • 71 multiple-choice and short-answer questions (must achieve score of 70% correct to pass)
  • 2 hours to complete exam
  • Use exam ID A00-281; required when registering with Pearson VUE.
  • Candidate must hold the SAS Certified Base Programmer for SAS 9 credential to take this exam. Otherwise, candidate should take the A00-280 exam.
Exam topics include:
The following exam objectives are subject to change during the development process and will be updated prior to exam registration.
  • 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).
  • 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.
    • 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
    • Access DICTIONARY Tables using the SQL procedure.
    • Examine and explore clinical trials input data (find outliers, missing vs. zero values, etc).
  • 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.
  • Apply Statistical Procedures for Clinical Trials
    • Use SAS procedures to obtain descriptive statistics for clinical trials data (FREQ, UNIVARIATE, MEANS, SUMMARY).
    • Use PROC FREQ to obtain p-values for categorical data (2x2 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.
    • 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 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.
  • 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.