What is the result if STOPOVER is specified and the record ends without finding all variable values?

When STOPOVER is specified in a DATA step, it indicates that processing should halt whenever an observation is encountered that does not contain all required variable values. This means that if a record ends and the program does not find all the expected values for its variables, the entire dataset processing will be interrupted for that observation. This behavior is typically used to ensure data integrity, as it prevents incomplete observations from being processed further.

The intent behind using STOPOVER is to avoid any assumptions about missing data that could potentially lead to misleading results. Instead of filling in default values or simply disregarding the incomplete observations, this approach clearly delineates when data issues arise, ensuring that the analyst pays attention to the problematic records.

This is contrasted with paths taken when not using STOPOVER; for instance, without it, the program would either continue processing with default values or might ignore only the incomplete observations, leading to a potentially flawed dataset. Thus, the specific function of STOPOVER to halt processing for entire records emphasizes its role in data quality control.