Clinical SAS Programmer Training

SAS Clinicals Training with Placement

Course Content:

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.