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’ve updated the R code for the enhanced K-M plot to include additions and improvements by Gil Thomas and Mark Cowley. Thanks fellows for the feedback and updates. http://statbandit.wordpress.com/2011/03/08/an-enhanced-kaplan-meier-plot/
I just updated my RStudio version to the latest, v.0.94.92 (will this asymptotically approach 1, or actually get to 1?). It was nice to see the number of improvements the development team has implemented, based I’m sure on community feedback. The team has, in my experience, been extraordinarily responsive to user feedback, and I’m sure 
I’ve often selected columns or rows of a data frame using grep or which, based on some property. That is inherently sound, but the trouble comes when you wish to remove rows or columns based on that grep or which call, e.g., which would remove columns with a .1 in the name. This is fine 
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 
We often see, in publications, a Kaplan-Meier survival plot, with a table of the number of subjects at risk at different time points aligned below the figure. I needed this type of plot (or really, matrices of such plots) for an upcoming publication. Of course, my preferred toolbox was R and the ggplot2 package. There 
As most followers of R-bloggers.com and the Twitter #rstats know by now, RStudio is a new open-source IDE for R that was beta-released yesterday. I have started putting it through its paces within my R workflow, and my impressions are more than favorable. I also tried it out on my home Linux server in server 
Last night at the DC R Users meetup, which was our largest meetup to date, I gave an introductory presentation on data munging, and spent a bit of time on the split-apply-combine paradigm that I use almost daily in my work. I talked mainly about the packages plyr and doBy, which I use a lot 
I’ve been working on a long-term (25+yr) longitudinal study of rheumatoid arthritis with my boss. He just walked in and asked if I could create a plot showing the trajectory of pain scores over time for each subject, separated by educational level (4 groups). Having now worked with ggplot2 for a while, and learning more 
Forest plots are most commonly used in reporting meta-analyses, but can be profitably used to summarise the results of a fitted model. They essentially display the estimates for model parameters and their corresponding confidence intervals. Matt Shotwell just posted a message to the R-help mailing list with his lattice-based solution to the problem of creating forest plots in R. I 
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
