This paper investigates a scenarios that occurs regularly in clinical trials when generating summary tables for categorical data; namely the need to display all possible categories for a CRF even when some categories are not present in the data.

The authors look at what we think is the most commonly used approaches to this problem, i.e. using PROC FREQ/SQL to count the data and forcing out the missing categories by merging the output with a dummy dataset. They then suggest an elegant alternative approach using PROC MEANS in combination with the COMPLETETYPES and PRELOADFMT options.

The paper also suggests how a similar approach can be used to derive total columns.

The paper was presented in the Coder’s Corner section of the PharmaSUG 2012 Conference in San Francisco.

It is available for download here, alternative link.

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