Includes a pretty interesting discussion of dealing with overdispersion in mixed-effects models (e.g., count models) by using individual-level fixed effects. It also includes a whole series of citations.
An example of R code that tests for a mediation relationship.
A somewhat hard-to-find-but-useful set of ggplot2 examples buried on Hadley Wickham's site.
Cute way of creating web visualizations in R that don't work in my new NoScript-enabled browser.
A bunch of R code to fit your power law distributions.
I'm a huge fan of data.table and I've used it a ton in my own work in the last year.
There should be a better way of finding your R package than searching though a page of short descriptions of all 2800 package.s But there isn't.
Answer: When considering which class to use, always choose the least complex class that will support the application. That is, use Date if possible, otherwise use chron and otherwise use the POSIX classes.
It's exactly what it sounds like. Good? Slightly horrifying?
Awesome (and very short) section of debugging: 1. Be liberal with the use of print (or cat()) statements in your functions when debugging them! 2. traceback() # can see the sequence of function calls 3. options(error = dump.frames) debugger() # permits you to see the values of objects in the various nested environments of the function calls
A new R module that lets you keep your data on disk.
The description of fitting coxph to time dependent data here seems to be better than any I've found yet.
I think this would be pretty easy to do with gpplot2, but Portfolio looks like its worth checking out too.
Has some decent functionality that I might be interested in some time, although I don't think I'm interested in it now.
