Below you find a collection of news announcements about my research and software. Most of the dates of the posts are the dates when they were published. Some of the dates are ficticious however, in so far as they do not indicate the date when I put them on my website but rather the date when the relevant presentation was made or the paper was published.
The recently published version 0.99.31.6 of the memisc package also contains an
%$$% operator that simplifies routine data preparation steps that hitherto would
involve calls to the function
within(). It is analogous to the operator
which is provided by the “magrittr” package, but is also defined by this
These operators are illustrated by the following code examples.
Version 0.99.31.6 of package “memisc” was recently (3rd March 2023) published on
CRAN. One of the
new features of this version is the
%if% operator which allows
to assign values to subsets of observations. To see how it
works, consider the following example:
I implemented this feature on suggestion from a colleague who missed such a feature for data preparation.
The package ‘RKernel’ allows you to run R in Jupyter notebooks etc. I have been working on the package on and off since summer 2021. I started because I was dissatisfied with the default rich output that the already existing IRkernel produces. Also, the help system seemed to be broken with version <= 1.3 of ‘IRkernel’ when used with a more recent version of R (>=4.3?).1
My new book “Data Management in R: A Guide for Social Scientists” is now in print and is announced by SAGE to appear on 26 December 2020, right on time for Boxing Day!
Supporting material can be found on the page “Data Management in R: A Guide for Social Scientists”.
I am currently working on a book chapter about “Sozialstruktur und Wahlverhalten in Ost- und Westdeutschland – Konvergenz, Divergenz oder Persistenz?” (Social Structure and Voting Behaviour in East and West Germany – Convergence, Divergence, or Persistence?). In this context I found the remarkable result shown in the following figure.
Our paper on “Multilevel Analysis with Few Clusters: Improving Likelihood-based Methods” is now published as an open access article by the British Journal of Political Science (Elff, Heisig, Schaeffer, and Shikano 2021), along with a comment by Daniel Stegmueller (Stegmueller 2020) and a response by us (Elff, Heisig, Schaeffer, and Shikano 2021).