Clinical SAS programming

Selection criteria

• Writes and runs SAS code on screen rather than only describing it
• Uses clinical-trial or patient-level example data where possible
• Explains why each step is written the way it is and checks the log
• Uses SAS Studio, SAS OnDemand or Base SAS rather than a point-and-click task wizard only
• Avoids course, certification or placement marketing and clinical SAS career-salary talk

What was rejected

28 candidates did not meet the course criteria.

• Demonstrates library creation strictly via GUI dialogs; does not cover the LIBNAME statement, dataset importing, or viewing datasets via PROC PRINT or the table viewer.
• Demonstrates SAS Viya Visual Analytics via point-and-click rather than SAS Studio with SAS code (LIBNAME, PROC PRINT/CONTENTS).
• Is SAS installation or licence help only
• Focuses primarily on observation filtering rather than variable creation, IF-THEN-ELSE logic, or KEEP/DROP statements.
• Does not demonstrate reading datasets via the SET statement, nor IF-THEN-ELSE conditional logic, nor DROP/KEEP statements.
• Does not cover reading existing datasets with SET, deriving new variables, IF-THEN-ELSE logic, or KEEP/DROP statements; focuses exclusively on raw data line-pointer controls.
• Only explains DATA step theory without running code; or is about PROC SQL or a different language
• Uses HR data rather than clinical trial data, uses an INFORMAT statement rather than the INPUT function, and does not compute a study day or age difference.
• Only lists format names without converting or calculating a date
• covers only character string functions unrelated to dates
• Only stacks datasets with SET without a BY merge
• Only stacks datasets with SET without a BY merge
• Only stacks datasets with SET without a BY merge
• Focuses primarily on PROC SQL Views and lacks table joins, summarization, and GROUP BY clauses required by the rubric.
• Lacks coverage of WHERE clauses, GROUP BY aggregations, and table joins.
• Does not cover WHERE clauses, GROUP BY summarization, or table joins.
• Does not cover WHERE filtering, GROUP BY summarisation, or table joins.
• This video covers handling missing observations in SAS using DATA step and PROC SQL, and does not demonstrate PROC FREQ or PROC MEANS.
• This video focuses specifically on the %STR macro quoting function and does not cover %MACRO, %MEND, or writing parameterized reusable macros.
• Only lists SDTM domains or variables without programming
• Only lists SDTM domains or variables without programming
• Only lists SDTM domains or variables without programming
• Only names ADaM dataset types without explaining ADSL or its derivation
• Only names ADaM dataset types without explaining ADSL or its derivation
• Shows basic frame formatting options on raw sashelp.class data rather than compiling a clinical demographic summary table across treatment arms.
• Focuses on automotive data (SASHELP.CARS) rather than clinical trial demographics or baseline characteristic tables, and does not demonstrate ODS output destinations like RTF or PDF.
• Focuses entirely on pagination in patient lab data listings rather than creating a demographics summary table.
• Does not teach building a full demographics or baseline characteristics summary table by treatment arm; focuses strictly on handling zero-observation edge cases.