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Archive of posts filed under the Political Science category.

The Use of Sampling Weights in Bayesian Hierarchical Models for Small Area Estimation

All this discussion of plagiarism is leaving a bad taste in my mouth (or, I guess I should say, a bad feeling in my fingers, given that I’m expressing all this on the keyboard) so I wanted to close off the workweek with something more interesting. I happened to come across the above-titled paper by […]

Message to Booleans: It’s an additive world, we just live in it

Boolean models (“it’s either A or (B and C)”) seem to be the natural way that we think, but additive models (“10 points if you have A, 3 points if you have B, 2 points if you have C”) seem to describe reality better—at least, the aspects of reality that I study in my research. […]

Damn, I was off by a factor of 2!

I hate when that happens. Demography is tricky. Oh well, as they say in astronomy, who cares, it was less than an order of magnitude!

Next Generation Political Campaign Platform?

[This post is by David K. Park] I’ve been imagining the next generation political campaign platform. If I were to build it, the platform would have five components: Data Collection, Sanitization, Storage, Streaming and Ingestion: This area will focus on the identification and development of the tools necessary to acquire the correct data sets for […]

Buggy-whip update

On 12 Aug I sent the following message to Michael Link, president of the American Association for Public Opinion Research.  (I could not find Link’s email on the AAPOR webpage but I did some googling and found an email address for him at nielsen.com.): Dear Dr. Link:A colleague pointed me to a statement released under your […]

Steven Pinker on writing: Where I agree and where I disagree

Linguist and public intellectual Steven Pinker recently published an article, “Why Academics Stink at Writing.” That’s a topic that interests me! Like Pinker, I’ve done a lot of writing, both for technical and general audiences. Unlike Pinker, I have not done research on linguistics, but I’ll do my best to comment based on my own […]

How to read (in quantitative social science). And by implication, how to write.

It all started when I was reading Chris Blattman’s blog and noticed this: One of the most provocative and interesting field experiments I [Blattman] have seen in this year: Poor people often do not make investments, even when returns are high. One possible explanation is that they have low aspirations and form mental models of […]

A question about varying-intercept, varying-slope multilevel models for cross-national analysis

Sean de Hoon writes: In many cross-national comparative studies, mixed effects models are being used in which a number of slopes are fixed and the slopes of one or two variables of interested are allowed to vary across countries. The aim is often then to explain the varying slopes by referring to some country-level characteristic. […]

Quantitative literacy is tough! Or, I had no idea that, in 1958, 96% of Americans disapproved of interracial marriage!

Mark Palko linked to this data-rich cartoon by Randall Munroe: And I was stunned, first by the data on interracial marriage and then, retrospectively, by my earlier ignorance of these data. Was approval of interracial marriage only 4% in 1958? I had no idea. I looked it up at the Gallup site and it seems […]

What do Rick Santorum and Andrew Cuomo have in common?

Besides family values, that is? Both these politicians seem to have a problem with the National Weather Service: The Senator: Santorum also accused the weather service’s National Hurricane Center of flubbing its forecasts for Hurricane Katrina’s initial landfall in Florida, despite the days of all-too-prescient warnings the agency had given that the storm would subsequently […]