Noam Ross has a great overview of making code go faster in R here, although a lot of the ideas (such as pre-allocation) apply to every language. My own tips are not that dissimilar--a little less complete but more specific.

Apply-style commands in R

Here's a quick table of what I think are the most useful apply-style commands in R:

Function	Input	Output	Best for
apply	Rectangular	Rectangular or vector	Applying function to rows or columns
lapply	Anything	List	Non-trivial operations on almost any data type
sapply	Anything	Simplified (if possible) or list	Same as lapply, but with simplified output
plyr::ddply	data.frame	data.frame	Applying function to groupings defined by variables

For alternatives to plyr, see this post on StackOverflow.

R scripts for analyzing survey data

Another site pops up with open code for analyzing public survey data: http://www.asdfree.com/ It will be interesting to see whether this gets used by the general public--given the growing trend of data journalism and so forth--versus academics. It is a useful resource for both.