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How to Handle Missing Values in SAS Datasets

One common way to handle missing values in SAS datasets is by using the 'MISSING' statement in the 'PROC MEANS' or 'PROC SUMMARY' procedures. This allows you to specify how missing values should be treated when performing calculations or summarizations.

Another approach is to use functions like 'COALESCE' or 'IFN' to replace missing values with specific values, such as zeros or averages, before running any analysis on the dataset.

Additionally, you can use the 'PROC SQL' procedure in SAS to identify and handle missing values by filtering them out or replacing them with appropriate values based on the context of your analysis.

By implementing these strategies, you can ensure that missing values in SAS datasets are treated appropriately, preventing any potential issues or inaccuracies in your analysis results.

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