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Duration, language, and format of Clinical Trials Programming Using SAS 9 Accelerated Version (A00-281) Exam

Format: Multiple choices, multiple answers

  • Number of questions: 70-75
  • Passing score: 70%
  • Language: English
  • Length of Examination: 2 hours

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SASInstitute A00-281 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Use SAS procedures to obtain descriptive statistics for clinical trials data
  • Identify the classes of clinical trials data
Topic 2
  • Use PROC TTEST to obtain p-values for continuous data
  • Describe the contents and purpose of define.xml
Topic 3
  • Utilize the log file to validate clinical trial data reporting
  • Access DICTIONARY Tables using the SQL procedure
Topic 4
  • Apply 'observation carry forward' techniques to clinical trials data
  • Create output data sets from statistical procedures
Topic 5
  • Use ODS and global statements to produce and augment clinical trials reports
  • Describe the structure and purpose of the CDISC ADaM data model
Topic 6
  • Identify and Resolve data, syntax and logic errors
  • Derive programming requirements from an SAP and an annotated Case Report Form

Reference: https://www.sas.com/en_us/certification/credentials/foundation-tools/clinical-trials-programmer/clinical-trials-programming-accelerated-exam.html

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Here are the topics of Clinical Trials Programming Using SAS 9 Accelerated Version (A00-281) Exam

Candidates must know the exam topics before they start of preparation. Because it will really help them in hitting the core. Our Clinical Trials Programming Using SAS 9 Accelerated Version A00-281 exam dumps will include the following topics:

Clinical Trials Process

  • Create output data sets from statistical procedures. Macro Programming for Clinical Trials
  • Obtain counts of events in clinical trials. Apply Statistical Procedures for Clinical Trials
  • Identify the classes of clinical trials data (demographic, lab, baseline, concomitant medication, etc.).
  • Describe the clinical research process (phases, key roles, key organizations).
  • Describe the contents and purpose of define.xml. Import and Export Clinical Trials Data
  • Describe the structure and purpose of the CDISC SDTM data model.
  • Describe the structure and purpose of the CDISC ADaM data model.
  • Apply categorization and windowing techniques to clinical trials data.
  • Examine and explore clinical trials input data (find outliers, missing vs. zero values, etc). Transform Clinical Trials Data
  • Use PROC FREQ to obtain p-values for categorical data (2x2 and NxP test for association).
  • Automate programs by defining and calling macros.
  • Apply ‘observation carry forward' techniques to clinical trials data (LOCF, BOCF, WOCF).
  • Explain the principles of programming validation in the clinical trial industry.
  • Use SAS procedures to obtain descriptive statistics for clinical trials data (FREQ, UNIVARIATE, MEANS, SUMMARY).
  • Use system options to debug macros and display values of macro variables in the SAS log (MPRINT, SYMBOLGEN, MLOGIC, MACROGEN). Report Clinical Trials Results
  • Calculate ‘change from baseline' results.
  • Identify key CDISC principals and terms.
  • Create and use user-defined and automatic macro variables.
  • Transpose SAS data sets.
  • Apply regulatory requirements to exported SAS data sets (SAS V5 requirements). Manage Clinical Trials Data
  • Utilize the log file to validate clinical trial data reporting.
  • Use PROC TTEST to obtain p-values for continuous data (one-sample, paired and two-sample t-tests).
  • Derive programming requirements from an SAP and an annotated Case Report Form.
  • Use ODS and global statements to produce and augment clinical trials reports. Validate Clinical Trial Data Reporting
  • Describe regulatory requirements (principles of 21 CFR Part 11, International Conference on Harmonization, Good Clinical Practices). Clinical Trials Data Structures
  • Use PROC REPORT to produce tables and listings for clinical trials reports.
  • Interpret a Statistical Analysis Plan.
  • Access DICTIONARY Tables using the SQL procedure.
  • Use programming techniques to validate clinical trial data reporting (PROC COMPARE, MSGLEVEL).
  • Identify and Resolve data, syntax and logic errors.

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