r

You're Already Ready: Zen and the Art of R Package Development

R packages make it easier to write robust, reproducible code, and modern tools in R development like usethis make it easy to work with packages. When you write R packages, you also unlock a whole ecosystem of tools that will make it easier to test, …

You're Already Ready: Zen and the Art of R Package Development

R packages make it easier to write robust, reproducible code, and modern tools in R development like usethis make it easy to work with packages. When you write R packages, you also unlock a whole ecosystem of tools that will make it easier to test, …

Data science as an atomic habit

Several years ago, I lived at the Zen Center of New York City, a Zen temple focused on supporting lay practitioners (folks who practice but also have jobs, families, and so on). Living at a Zen center is inherently intensive. You follow the temple schedule—morning and evening meditation, work and meals together, and regular meditation retreats—as well as managing your other responsibilities. Yet, there’s an ease to practicing meditation in such a place.

Causal Inference in R

In both data science and academic research, prediction modeling is often not enough; to answer many questions, we need to approach them causally. In this workshop, we’ll teach the essential elements of answering causal questions in R through causal …

Data manipulation, visualization, and reproducible documents with R and the Tidyverse

Recent developments by the R community have revolutionized the data analysis pipeline in R, from manipulating and visualizing data to communicating results. Our workshop will provide hands-on training in tools from the tidyverse ecosystem, using real …

Mastering R for Epidemiology

A week-long, intensive introduction to R remotely offered at the Berlin School of Public Health at Charité – Universitätsmedizin Berlin. The course is for researchers, public health professionals, epidemiologists, and clinicians who want to improve …

Causal Inference in R

In both data science and academic research, prediction modeling is often not enough; to answer many questions, we need to approach them causally. In this workshop, we’ll teach the essential elements of answering causal questions in R through causal …

Why should I use the here package when I'm already using projects?

Estimating sample size for precision: precisely 0.1.0

I’m pleased to announce that precisely 0.1.0 is now on CRAN! precisely is a study planning tool to calculate sample size based on precision rather than power. Power calculations focus on whether or not an estimate will be statistically significant; calculations of precision are based on the same principles as power calculation but turn the focus to the width of the confidence interval. precisely currently supports sample size calculations for risk differences, rate differences, risk ratios, rate ratios, and odds ratios.

Replicating a New York Times Table of Swedish COVID-19 deaths with gt

I recently read an article in the New York Times about excess deaths in Sweden during the coronavirus outbreak. As opposed to many of its neighbors, Sweden did not do a general lockdown; instead, it (controversially) strove to systematically develop herd immunity. However, current data suggest that excess deaths (the number of deaths above the usual number) in Sweden are higher than many of its neighbors that enacted early, stricter lockdowns.