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Archive of posts filed under the Political Science category.

Weisburd’s paradox in criminology: it can be explained using type M errors

This one (with Torbjørn Skardhamar, and Mikko Aaltonen) goes out to all the criminologists out there. . . . Here’s the story: Simple calculations seem to show that larger studies should have higher statistical power, but empirical meta-analyses of published work in criminology have found zero or weak correlations between sample size and estimated statistical […]

“What we know and don’t know about the 2016 election—and beyond” (event at Columbia poli sci dept next Monday midday)

On Monday 25 Sep, 12:10-1:45pm, in the Playroom (707 International Affairs Bldg): “What we know and don’t know about the 2016 election—and beyond” (discussion led by Bob Shapiro, Bob Erikson, me, and other Columbia political science faculty)

Maybe this paper is a parody, maybe it’s a semibluff

Peter DeScioli writes: I was wondering if you saw this paper about people reading Harry Potter and then disliking Trump, attached. It seems to fit the shark attack genre. In this case, the issue seems to be judging causation from multiple regression with observational data, assuming that control variables are enough to narrow down to […]

Where does the discussion go?

Jorge Cimentada writes: In this article, Yascha Mounk is saying that political scientists have failed to predict unexpected political changes such as the Trump nomination and the sudden growth of populism in Europe, because, he argues, of the way we’re testing hypotheses. By that he means the quantitative aspect behind science discovery. He goes on […]

New Zealand election polling

Llewelyn Richards-Ward writes: Here is a forecaster apparently using a simulated (?Bayesian) approach and smoothing over a bunch of poll results in an attempt to guess the end result. I looked but couldn’t find his methodology but he is at University of Auckland, if you want to track him down… As a brief background, we […]

American Democracy and its Critics

I just happened to come across this article of mine from 2014: it’s a review published in the American Journal of Sociology of the book “American Democracy,” by Andrew Perrin. My review begins: Actually-existing democracy tends to have support in the middle of the political spectrum but is criticized on the two wings. I like […]

Causal inference using data from a non-representative sample

Dan Gibbons writes: I have been looking at using synthetic control estimates for estimating the effects of healthcare policies, particularly because for say county-level data the nontreated comparison units one would use in say a difference-in-differences estimator or quantile DID estimator (if one didn’t want to use the mean) are not especially clear. However, given […]

Job openings at online polling company!

Kyle Dropp of online polling firm Morning Consult says they are hiring a bunch of mid-level data scientists and software engineers at all levels: About Morning Consult: We are interviewing about 10,000 adults every day in the U.S. and ~20 countries, we have worked with 150+ Fortune 500 companies and industry associations and we are […]

“How conditioning on post-treatment variables can ruin your experiment and what to do about it”

Brendan Nyhan writes: Thought this might be of interest – new paper with Jacob Montgomery and Michelle Torres, How conditioning on post-treatment variables can ruin your experiment and what to do about it. The post-treatment bias from dropout on Turk you just posted about is actually in my opinion a less severe problem than inadvertent […]

God, goons, and gays: 3 quick takes

Next open blog spots are in April but all these are topical so I thought I’d throw them down right now for ya. 1. Alex Durante writes: I noticed that this study on how Trump supporters respond to racial cues is getting some media play, notably over at Vox. I was wondering if you have […]

Do we trust these data on political news consumption?

Mark Palko writes: The Monkey Cage just retweeted this but some of the numbers look funny. “This” is a paper, “The Myth of Partisan Selective Exposure: A Portrait of the Online Political News Audience,” by Jacob Nelson and James Webster, which who write: We explore observed online audience behavior data to present a portrait of […]

We were unfair to traditional pollsters

A couple days ago, Slate ran an article by David Rothschild and myself, “We Need to Move Beyond Election-Focused Polling,” in which we wrote about various aspects of the future of opinion surveys. One aspect of this article was misleading. We wrote: And instead of zeroing in on elections, we should think of polling and […]

Gigo update (“electoral integrity project”)

Someone sent me this note: I read your takedown of the EIP on Slate and then your original blog post and the P. Norris response. I wanted to offer a couple of points. First, as you can see below, I was asked to be one of the ‘experts.’ I declined. I think we all can […]

The Groseclose endgame: Getting from here to there.

A few years ago, I wrote the following regarding political scientist Tim Groseclose’s book on media bias: Groseclose’s big conclusion is that in the absence of media bias, the average American voter would be positioned at around 25 on a 0-100 scale, where 0 is a right-wing Republican and 100 is a left-wing Democrat. . […]

“Mainstream medicine has its own share of unnecessary and unhelpful treatments”

I have a story and then a question. The story Susan Perry (link sent by Paul Alper) writes: Earlier this week, I [Perry] highlighted two articles that exposed the dubious history, medical ineffectiveness and potential health dangers of popular alternative “therapies.” Well, the same can be said of many mainstream conventional medical practices, as investigative […]

Using statistical prediction (also called “machine learning”) to potentially save lots of resources in criminal justice

John Snow writes: Just came across this paper [Human Decisions and Machine Predictions, by Jon Kleinberg, Himabindu Lakkaraju, Jure Leskovec, Jens Ludwig, and Sendhil Mullainathan] and I’m wondering if you’ve been following the debate/discussion around these criminal justice risk assessment tools. I haven’t read it carefully or fully digested the details. On the surface, their […]

Fake polls. Not new.

Mark Palko points me to this article by Harry Enten about a possibly nonexistent poll that was promoted by an organization or group or website called Delphi Analytica. Enten conjectures that the reported data were not fabricated but they’re not a serious poll either but rather some raw undigested output from a Google poll. This […]

Irish immigrants in the Civil War

I was cc-ed on a series of emails on a topic I know nothing about, maybe because I’m on the political science faculty here, I don’t know. Anyway, there was some statistical content here so I thought I’d share with you. The email is from James McManus: Analysis of the Civil War Immigrant problem McPherson’s […]

The Pandora Principle in statistics — and its malign converse, the ostrich

The Pandora Principle is that once you’ve considered a possible interaction or bias or confounder, you can’t un-think it. The malign converse is when people realize this and then design their studies to avoid putting themselves in a position where they have to consider some potentially important factor. For example, suppose you’re considering some policy […]

“Social Media and Fake News in the 2016 Election”

Gur Huberman asks what I think about this paper, “Social Media and Fake News in the 2016 Election,” by Hunt Allcott and Matthew Gentzkow. I haven’t looked at in detail my quick thought is that they’re a bit too “mechanistic” as the effect of fake news is not just the belief in each individual story […]