Pocketbook costs of software

I have always been provided SAS as part of my job, so I never really realized how much it cost. I’ve bought Stata before, and of course R :). I recently found out how much a reasonable bundle of SAS modules along with base SAS costs per year per seat, at least under the GSA. I tried finding out how much IBM SPSS is for a comparable bundle, but their web page was “not available”. Stata costs in the ballpark of $1700 (for a permanent license of Stata/SE) or $845 for an annual license. SAS costs over 5 times that per seat for similar functionality (Ouch!!). R, with its quirks but with similar if not enhanced functionality in a lot of areas, is of course, freely downloadable. 

Matlab is another software I’ve bought as part of my job. For a reasonable bundle, in an academic setting, it is close to $3000. Of course, here it’s a bit easier to pick and choose, since I don’t need most of the modules which are of more interest to engineers.

SAS, R and categorical variables

One of the disappointing problems in SAS (as I need PROC MIXED for some analysis) is to recode categorical variables to have a particular reference category. In R, my usual tool, this is rather easy both to set and to modify using the  relevel command available in base R (in the stats package). My understanding is that this is actually easy in SAS for GLM, PHREG and some others, but not in PROC MIXED. (Once again I face my pet peeve about the inconsistencies within a leading commercial product and market “leader” like SAS). The easiest way to deal with this, I believe, is to actually create the dummy variables by hand using ifelse statements and use them in the model rather than the categorical variables themselves. If most of the covariates are not categorical, this isn’t too burdensome.

I’m sure some SAS guru will comment on the elegant or “right” solution to this problem.