I have long found the quantitative side of political science research deeply fascinating. The various estimation methods, sampling distributions and arguments about Bayesian vs Frequentist approaches amuse me to no end. The more detail provided about methodology and analysis in an article the better. However, I also recognize that my deep enjoyment of these aspects of political science make me a bit of an outlier (at least in some parts of Europe!).
A friend of mine who also happens to be a PhD student at UCD (link) and happens to study electoral behavior and turnout has spent many an hour trying to show me the light; that our research is at its best when it can be conveyed to the “real people”. It has been a difficult education for me, but I’m slowly coming around to a position in which I agree that, for this field, there should always be something of value that can be taken from our research and conveyed in a clear and interesting way to people who don’t care that my OLS is BLUE (I know, they make me sad too).
Obviously I am slightly exaggerating my position. As my research has often been rooted in the politics of the environment it is nearly impossible to separate out either a normative or real-world aim to what I’m doing. In fact, I have broad plans for the “real-world” applicability of my research, but I leave that for another time. Nonetheless, our conversations have been most useful in helping me design my graphs more clearly. As another friend (link) described him, he has an Andrew Gelman-like ability to nit-pick any graph to pieces. I’ll steal the concept, creative destruction, to describe his talent.
Kastellec and Leoni have an article which is very much on point for these discussion from an actual practice perspective. They detail an interesting way to replace simple and complex tables with concise graphs. An excellent read, and one which I have taken to heart and incorporated into my methods. While I think they have demonstrated an incredibly useful technique for displaying table results clearly with coefficients and confidence intervals, I’m not sure my friend has been sold. If I wanted to completely misrepresent his position to provoke a response I would characterize his position as “if it’s not a barplot I don’t want to see it”.
I can imagine this debate never being completely settled which is, I think, a good thing. Having people you respect constantly pushing you to provide greater clarity can only strengthen your argument, and hopefully, I can eventually convince him that without confidence intervals we have nothing…
Below is a very basic example with invented data just to convey the idea:
(The points on the graph are the coefficients and the solid line represents the 95% confidence interval. Obviously, when the CI includes the vertical line at zero, the null, that Beta_i equals zero, cannot be excluded.)
Kastellec, J.P. & Leoni, E.L., 2007. Using Graphs Instead of Tables in Political Science. Perspectives on Politics, 5(04), p.755-771.