Are You Missing Out? Working with Missing Values to Make the Most of What is not There

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Abstract

Everyone uses and works with missing values, however many SAS® programmers are unaware of the variety of tools, options, and techniques associated with using missing values. Did you know that there are 28 types of numeric missing values? Did you know that the numeric missing value (.) is neither the smallest or largest possible numeric missing value? Are you aware of the System options, DATA step functions, and DATA step routines that specifically deal with missing values? Do you understand how the macro null value is the same, and different from DATA step missing values? Are you aware that observations with missing classification variables may or may not be excluded from analyses depending on the procedure and various options?.


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