I’m at the useR! conference so I’ll be blogging every day with at least one thing that I learned.
The first thing, which I think I half-knew and had also half-learned from bitter experience, is that all the R experts seem to use Linux, Ubuntu in the case of the two people who ran the tutorials I attended today. I already dual-boot Windows and Linux and I think over time I’m going to reduce Windows to the operating system on which I play games and check my work email (which I can only get to run on Windows due to security software requirements).
The second thing is a neat way to plot regression when the outcome is binary. I’ve often wondered how I can visualise what’s going on when you have a horrible graph that looks like this:
It’s very simple, and I now know thanks to Douglas Bates’s excellent lme4 tutorial. Draw a graph like this (points are suppressed, you can include them if you want):
Just a few lines of code for the whole kit and caboodle:
library(lattice) Outcome=sample(0:1, 100, replace=TRUE) # simulate data Predictor=runif(100)*100 # simulate data plot(Predictor, Outcome) # ugly graph xyplot(Outcome~ Predictor, type = c("g", "smooth"), ylab = "Outcome", xlab = "Predictor") # useful graph
You can simulate the data properly so that there is an actual correlation if you want to (e.g. here) but I thought you’d spare me the bother- you get the idea.
Oh yes, I did learn one other thing today- they’re called packages, not libraries. One for the pedants among you.