Factors have huge benefits over character data in SAS. For a series regulatory filings, I had miles of SAS code to compute KxK tables where all the cells must show up. For example, if one of the levels of one of the variables was never observed, the corresponding row or column would not show up in proc freq. The basic way around this was to get all possible combinations of the variables and assign each cell to have a row count of 0.00000001. Then you would merge this data with the real counts. The missing row/columns would show up since they had data, but it was below the printing threshold of proc freq. Hoepfully, they have added a feature to do this.
You can imagine how much work the test documents were for that macro. Contrast that with a simple call to the canned table function in R. And people think that SAS has an advantage when it comes to "validation"... Also, I always think about having a real programming language with namespaces, object-orientation, real functions, scoping, etc. This is very important and often under-recognized. For example, I've seen SAS macros called inside of SAS macros; this can be dangerous because the data lives in the same area and if two macros had a dataset with the same name the data would be over-written. -- Max ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
