SAS Certified Clinical Trials Programmer Using SAS 9 A00-282 Practice Exam

SAS Certified Clinical Trials Programmer Using SAS 9 A00-282 Practice Exam

The SAS Certified Clinical Trials Programmer Using SAS 9 (A00-282) exam validates a candidate's knowledge and skills in programming for clinical trials using SAS 9. It assesses your ability to perform common clinical trial programming tasks like:

• Data manipulation
• Variable creation
• Analysis datasets creation
• Report generation

Who Should Take This Exam?

This exam is ideal for individuals who:

• Have experience in programming with SAS 9
• Are involved in clinical trial data management and analysis
• Aspire to validate their expertise in SAS programming for clinical trials
• Seek career advancement in the clinical research field

Exam Eligibility Criteria:

Candidates who succeed should:

• Fulfill the prerequisite conditions by holding either the Base Programming Specialist or the Advanced Programming Professional certifications.
• Complete the suggested training OR possess comparable experience.
• Have a minimum of six months of experience as a clinical trials programmer utilizing SAS software.

Exam Details

• Exam Name: SAS Certified Professional: Clinical Trials Programming Using SAS 9.4
• Exam Code: A00-282
• Number of Questions: 60-70 multiple-choice and short answer questions
• Passing Score: 68%
• Time: 1 hour 50 minutes

Course Outline

The exam covers the following topics:

Domain 1: Learn about Clinical Trials Process – 5%

• Describe the clinical research process (phases, key roles, key organizations).
• Derive programming requirements from an SAP and an annotated Case Report Form.

Domain 2: Clinical Trials Data Structures – 10%

• Identify the clinical trials domains.
• 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.
• Trace data through the full programming process, from raw data to any of the mapped domains.

Domain 3: Learn about Regulatory Submissions – 5%

• Apply regulatory requirements to exported SAS data sets (SAS V5 requirements).
• Describe the contents and purpose of define.xml.

Domain 4: Understand Manage Clinical Trials Data – 5%

• Access DICTIONARY Tables using the SQL procedure.
• Examine and explore clinical trials input data (find outliers, missing vs. zero values).

Domain 5: Transform or Summarize Clinical Trials Data – 15%

• Derive variables by applying categorization and windowing techniques to existing variables.
• Store dates in a form that is acceptable for use with clinical trials
• Reshape SAS data sets
• Calculate 'change from baseline' results.
• Obtain counts of events in clinical trials.
• Use FIRST./LAST. variables

Domain 6: Apply Statistical Procedures for Clinical Trials – 15%

• Use SAS procedures to obtain descriptive statistics for clinical trials data (FREQ, UNIVARIATE, MEANS, SUMMARY).
• Given information on data types (categorical vs. quantitative), determine whether a procedure can produce the requested analysis.
• Given sample code from a statistical procedure, identify syntax and/or semantic errors. (PROC FREQ, PROC TTEST, GLM, REG, )
• Create output data sets from statistical procedures.
• Follow instructions to be able to program for both Safety and Efficacy data.

Domain 7: Macro Programming for Clinical Trials – 15%

• Create macro variables and set macro parameters.
• Access user-defined and automatic variables.
• Automate repeated tasks by defining and calling macros.
• Use system options to debug macros and display values of macro variables in the SAS log (MPRINT, SYMBOLGEN, MLOGIC,).

Domain 8: Understand about Report Clinical Trials Results – 10%

• Use PROC REPORT to produce tables and listings for clinical trials reports.
• Use ODS statements to produce and augment clinical trials reports.
• Create and work with graphs

Domain 9: Validate Clinical Trial Data Reporting – 20%

• 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).
• Determine why two independent validation programs led to a different result.
• Identify elements that are not validated when comparing via PROC COMPARE. (titles, footnotes, and attributes such as formats or labels depending on how they are added to a PROC-like REPORT)
• Identify and Resolve data, syntax, and logic errors.