Getting a legend in ggplot2 when the aesthetic value is a constant instead of a variable can be tricky. I go through an example of a situation where this might be useful and show how to first get a legend and then how to "prettify" that legend.

Extending my simulation examples into the world of generalized linear models, I simulate Poisson data to explore what a quadratic relationship looks like on the scale of the data when fitting a generalized linear model with a log link.

In this post I delve into the details of the R functions I've been using in my simulation examples, focusing on the replicate() function and the map family of functions from the purrr package. I spend a little time showing the parallels between the replicate() function and a for() loop.

Unstandardizing coefficients in order to interpret them on the original scale can be needed when explanatory variables were standardized to help with model convergence when fitting generalized linear mixed models. Here I show one approach to unstandardizing for a generalized linear mixed model fit with lme4.

Ariel Muldoon

I currently work as a consulting statistician, advising natural and social science researchers on statistics, statistical programming, and study design. I create and teach R workshops for applied science graduate students who are just getting started in R, where my goal is to make their transition to a programming language as smooth as possible. See my workshop materials at my website.