I've only read through the chapter on transformations but this seems likely a truly excellent resource. Gratis for personal use.
The description of fitting coxph to time dependent data here seems to be better than any I've found yet.
Combination example code for common things and tutorial.
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.
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.
Simple R package to format model objects in a regression table like the kind that everyone reporting models wil need to do. Nice start even if one wants to modify things after that. Based on PoliSci publications but looks pretty standard for other social sciences.
I think this would be pretty easy to do with gpplot2, but Portfolio looks like its worth checking out too.
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.
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
It's exactly what it sounds like. Good? Slightly horrifying?
A bunch of R code to fit your power law distributions.
Awesome resource. I can't believe I've only found this now.
Looks like an awesome conference, although it seems it will conflict with the Knight News conference. Damn.
A new R module that lets you keep your data on disk.
I'm a huge fan of data.table and I've used it a ton in my own work in the last year.
