Last Thursday I watched Wolfgang Viechtbauer’s stream on Twitch. Wolfgang spoke about linear regression. (If you’re interested in the results: Wolfgang lists the R-code he wrote during the stream at https://www.wvbauer.com/doku.php/live_streams.)

During the stream we had an example with one categorical and one numeric predictor and we built a model with interaction between these two predictors. So the result is a straight line for each value of the categorival group.

The question was if it makes a difference if you build a simple linear model for each group.

So let’s look at it.

I made another small update to my SARS-CoV-2 Shiny App.

As the discussion in Germany about whether to open schools and shops starts again I was wondering how I could visualize a simple prediction of future infections.

I’m working on an R-package to access the data of a web service. So I have to handle large data I get back from an API call. The result is encoded in JSON-format which itself results in a large list of lists (of lists).

But I want to convert these lists of lists into a data.frame or tibble. Sounds easy …. Here are the caveats I came across.

I’ve updated my Shiny App slightly. Because of the appearence of the mutation B 1.1.7 I want to see the current R-value, the current reproduction rate of the virus per Landkreis or Bundesland.

Lately I’ve had the problem that ggplot2-plots were missing in my blogdown-posts.

I discovered that this problem only occurs when I used .Rmarkdown instead of .Rmd.