Time after time: calculating the autocorrelation function for uneven or grouped time series

Checking for autocorrelation must be done carefully when some observations are missing from a time series or the time series is measured for independent groups. I show an approach where I pad the dataset with NA via tidyr::complete() to fill in any missed sampling times and make sure groups are considered independent prior to calculating the autocorrelation function.

Unstandardizing coefficients from a GLMM

Unstandardizing coefficients in order to interpret them on the original scale is often necessary when explanatory variables were standardized to help with model convergence when fitting generalized linear mixed models. Here I show one automated approach to unstandardize coefficients from a generalized linear mixed model fit with lme4.

Fiesta 2017 gas mileage

Since January is the month for analyzing last year's data, I take a quick look at my 2017 gas mileage in my commuter car (Fiesta! 🎆). I use package googlesheets for reading data, skimr for a quick summary of the dataset, and ggplot2 for plotting.

Ariel Muldoon

I currently work as an applied statistician in aviation and aeronautics. In a previous role as a consulting statistician in academia I created and taught R workshops for applied science graduate students who are just getting started in R, where my goal was to make their transition to a programming language as smooth as possible. See these workshop materials at my website.