A00-280: SAS Certified Clinical Trials Programming Using SAS 9

Successful candidates should have experience in:

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  • Clinical trials process.
  • Accessing, managing and transforming clinical trials data.
  • Statistical procedures and macro programming.
  • Reporting clinical trials results.
  • Validating clinical trial data reporting.

SAS A00-280 Exam Summary:

Exam Name SAS Certified Clinical Trials Programming Using SAS 9
Exam Code  A00-280
Exam Duration  180 minutes
Exam Questions  95-100
Passing Score  70%
Exam Price  $180 (USD) 
Books  SAS Programming 1: Essentials
SAS Programming 2: Data Manipulation Techniques
SAS Macro Language 1: Essentials
SAS Report Writing 1: Essentials
Statistics 1: Introduction to ANOVA, Regression, and Logistic Regression
Sample Questions  SAS Clinical Trials Programming Certification Sample Question 
Practice Exam  SAS Clinical Trials Programming Certification Practice Exam

SAS A00-280 Exam Topics:

Objective Details 
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
– 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 (2×2 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.