Matthew Keller wrote: > Hi all, > > I'm giving a talk in a few days to a group of psychology faculty and > grad students re the R statistical language. Most people in my dept. > use SAS or SPSS. It occurred to me that it would be nice to have a few > concrete examples of things that are fairly straightforward to do in R > but that are difficult or impossible to do in SAS or SPSS. However, it > has been so long since I have used either of those commercial products > that I am drawing a blank. I've searched the forums and web for a list > and came up with just Bob Muenchen's comparison of general procedures > and Patrick Burns' overview of the three. Neither of these give > concrete examples of statistical problems that are easily solved in R > but not the commercial packages. > > Can anyone more familiar with SAS or SPSS think of some examples of > problems that they couldn't do in one of those packages but that could > be done easily in R? Similarly, if there are any examples of the > converse I would also be interested to know. > > Best, > > Matt >
Here is a simple thing that is easy to do in R or S-Plus but difficult in SAS or SPSS: Compute the number of subjects having age below the mean age sum(age < mean(age)) Here is something not quite so simple that is very difficult to do in SPSS or SAS. Show descriptive statistics for every variable in a data frame that is numeric and has at least 10 unique values. v <- sapply(mydata, function(x) is.numeric(x) && length(unique(x)) >= 10) summary(mydata[v]) -- Frank E Harrell Jr Professor and Chair School of Medicine Department of Biostatistics Vanderbilt University ______________________________________________ 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.