How does the SAS software handle missing values in a dataset?

When working with datasets in SAS, the software provides several ways to handle missing values:

1. Excluding Missing Values: SAS allows you to exclude observations with missing values using the `DROP` or `WHERE` statements.
2. Replacing Missing Values: You can replace missing values with a specific value using functions like `COALESCE` or `MISSING` in SAS.
3. Imputing Missing Values: SAS also offers various imputation techniques such as mean imputation or predictive modeling to fill in missing values.
4. Ignoring Missing Values: Some SAS procedures automatically ignore missing values when performing calculations or analyses.

Overall, SAS provides flexibility in handling missing values, allowing users to choose the best approach based on their specific data and analysis requirements.