SAS® Clinical Trials Programmer Certification Exam   

Below is a collection of SAS® papers to help prepare for the SAS® Clinical Trials Programmer Certification Exam.  See also New Clinical Programmer and SAS Certification ExamMind map.  See scope and practice test and sample test CDISC interview questions. See SAS Base reference sheet. See SAS Syntax reference sheet.

SAS Institute Exam Details

(24 hours) 
Certification Exam Topic

SAS® Savvy Reference 
 0.5 hour  

I. Clinical Trials Process
New Clinical SAS® Programme

Clinical Data Management

Regularory and Project Management

 6 hours  II. Clinical Trials Data Structures

 CDISC Strategies
 1 hours


 III. Import and Export Clinical Trials Data

 Data Access 

 Data Step and Merge

 Proc Import, Proc Export

 2 hours




IV. Manage Clinical Trials Data

 Lab Data

 Data Step (Do Loops, Arrays, Functions)

 Proc Transpose

 Proc Print

 Proc Contents

 Proc Freq

 0.5 hour  V. Transform Clinical Trials Data

 SAS Functions/Formats
 2 hours



VI. Apply Statistical Procedures for Clinical Trials

 SAS Statistical Analysis

 Proc Means/Summary

Commonly Used:

Continuous - ANCOVA and Survival analysis

Categorical - Chi Square, McNemar's Test and Rank Test

 2 hours  VII. Macro Programming for Clinical Trials

 SAS Macro Programming
 4 hours



 VIII. Report Clinical Trials Results

 Clinical Data Reporting

 Proc Report

 Proc SQL


 Statistical Graphs 

 4 hours


IX. Validate Clinical Trial Data Reporting

 Clinical Data Validation 

 Proc Tabulate

 Debugging Programs

 Proc Compare 

 4 hours  X. Other Topics

 SAS Base/Advanced Certification

 SAS Dates     


I. Clinical Trials Process

Describe the clinical research process (phases, key roles, key organizations)

Interpret a Statistical Analysis PlanTraining Statistical Programmers on SAP Review Skills, Sascha Ahrweiler
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)


II. 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

Implementation of the CDISC SDTM at the Duke Clinical Research Institute, Jack Shostak
Describe the structure and purpose of the CDISC ADaM data model

From SAP to ADaM: The Nuts and Bolts, Nancy Brucken, Paul Slagle
Describe the contents and purpose of define.xmlCreating a define.xml file for ADaM and SDTM, John H. Adams

III. 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)


IV. 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)


V. Transform Clinical Trials Data

Process data using DO LOOPSHow to Use ARRAYs and DO Loops: Do I DO OVER or Do I DO i?, Jennifer L Waller
Process data using SAS arrays

Arrays by example, Diana Suhr
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)

 Statisical Analysis (impute)
Calculate 'change from baseline' results

Obtain counts of events in clinical trials


VI. 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


VII. 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)

The Macro Debugging Primer, Frank DiIorio

VIII. Report Clinical Trials Results

Use PROC REPORT to produce tables and listings for clinical trials reports

Seven Steps to Regulatory Publication Style With Proc Report. Dennis Gianneschi
Use ODS and global statements to produce and augment clinical trials reports


IX. Validate Clinical Trial Data Reporting
Explain the principles of programming validation in the clinical trial industry

The 5 Most Important Clinical SAS Programming Validation Steps, Brian C. Shilling
Utilize the log file to validate clinical trial data reporting
Errors, Warnings, and Notes (Oh My) A Practical Guide to Debugging SAS Programs, Susan J. Slaughter, Lora D. Delwiche
Use programming techniques to validate clinical trial data reporting (PROC COMPARE, MSGLEVEL)

“How Does Your Data Compare?”, SAS’s COMPARE PROCEDURE, Jenna Heyen
Identify and Resolve data, syntax and logic errors


Be a Dead Cert for a SAS® Cert How to prepare for the most important SAS Certifications in the
Pharmaceutical Industry, Hannes Engberg Raeder

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