How to Measure Agreement, Consensus, and Polarization in Ordinal Data

A new working paper with Clem Aeppli on SocArXiv. We look at different measures to capture agreement, consensus, polarization, whatever you want to call it — in ordinal data. Using simulations and an empirical example, we show commonalities and differences between measures. The paper ends with recommendations for researchers wanting to measure consensus, agreement — whatever — in ordinal data.

Aeppli, Clem, and Didier Ruedin. 2022. ‘How to Measure Agreement, Consensus, and Polarization in Ordinal Data’. SocArXiv. https://doi.org/10.31235/osf.io/syzbr.

Ruedin, Didier. 2022. ‘Agrmt: Agreement A’. R. CRAN. http://agrmt.r-forge.r-project.org/.

Measuring Polarization Updated

I have just updated my R-package to measure agreement, polarization, dispersion — whatever you want to call it — in ordered rating scales to R-Forge. Version 1.40 includes more extensive documentation and a long due update of the package vignette. I’ll push it to CRAN in a moment. Every time I work on this package, it strikes me how many times the ‘problem’ has been solved, how different the approaches are, and sadly how often standard deviations are still used.

Calculating Agreement, Consensus, Polarization in R

I have just uploaded a new version of the R package agrmt to R-Forge. The package implements various measures to enumerate the degree of agreement, consensus, or polarization among respondents. Apart from van der Eijk’s Agreement “A”, there are a range of other measures proposed in the literature.

New Version of R Package agrmt

This week, a new version of the R package agrmt saw the light of day. I have been contacted because one of the functions in the package didn’t produce the right answers. I really appreciate this (the contacting), because it allowed me to fix the code. It was a matter of mixing up i and j. The first reaction in this case is always the worst: what if I got it all wrong? What if I can’t find the bug? To me, fixing code in my packages is important — not because of the undeniable satisfaction from getting it right — but because it is a small way to give back to the (virtual) community that gave us R and the many packages that come along with it.

The package, by the way, implements measures of agreement (consensus) in ordered rating scales, especially Cees van der Eijk’s (2001) measure of agreement A, but also measures of consensus (dispersion) by Leik, Tatsle and Wierman, Blair and Lacy, Kvalseth, and Berry and Mielke. Moreover, it implements Galtung’s AJUS for R.