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Clinical Trials Process

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

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