Clinical Trials Programming Using SAS 9 – Accelerated Version  A00-281



Clinical Trials Programming Using SAS 9 – Accelerated Version
Required ExamCandidates 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 ExamCandidates 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.