Posts

August 31, 2014

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7:14 PM | 4S / ESOCITE JOINT MEETING: “SCIENCE IN CONTEXT(S): SOUTHS AND NORTHS”
A report I wrote on this massive conference for my department’s website (link pending).  Thanks to Sara Peres for input. “A new formal collaboration in STS begins now”.  So opened the 172-page programme for the inaugural joint meeting between the … Continue reading →

August 30, 2014

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5:59 PM | Heroin’s Anthrax Problem
This may come as a total shock, but pure forms of illicit drugs can be hard to come by. Certain controlled substances are frequently adulterated, if not outright contaminated, by products that range from the household to the industrial to the pharmaceutical. Of course, some substances are more easily, frequently, and profitably adulterated than others: cocaine […]The post Heroin’s Anthrax Problem appeared first on Body Horrors.
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3:00 PM | On deck this month
Bad Statistics: Ignore or Call Out? Questions about “Too Good to Be True” I disagree with Alan Turing and Daniel Kahneman regarding the strength of statistical evidence Why isn’t replication required before publication in top journals? Confirmationist and falsificationist paradigms of science How does inference for next year’s data differ from inference for unobserved data […] The post On deck this month appeared first on Statistical Modeling, Causal Inference, […]

August 29, 2014

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1:57 PM | Avoiding model selection in Bayesian social research
One of my favorites, from 1995. Don Rubin and I argue with Adrian Raftery. Here’s how we begin: Raftery’s paper addresses two important problems in the statistical analysis of social science data: (1) choosing an appropriate model when so much data are available that standard P-values reject all parsimonious models; and (2) making estimates and […] The post Avoiding model selection in Bayesian social research appeared first on Statistical Modeling, Causal Inference, and […]
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9:58 AM | Cadet Impressions: Tech Entrepreneurs in Tanzania Part 3
During our visit to Dar es Salaam, the cadets on my team, Molly Prins, Jake Moffatt, and Charlie Braman, spent time interacting with, and interviewing young tech entrepreneurs. These interviews are the raw data input for our “Developing Network Models … Continue reading →

August 28, 2014

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11:52 PM | When we talk about the “file drawer,” let’s not assume that an experiment can easily be characterized as producing strong, mixed, or weak results
Neil Malhotra: I thought you might be interested in our paper [the paper is by Annie Franco, Neil Malhotra, and Gabor Simonovits, and the link is to a news article by Jeffrey Mervis], forthcoming in Science, about publication bias in the social sciences given your interest and work on research transparency. Basic summary: We examined […] The post When we talk about the “file drawer,” let’s not assume that an experiment can easily be characterized as producing strong, […]
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1:37 PM | Pre-election survey methodology: details from nine polling organizations, 1988 and 1992
This one from 1995 (with D. Stephen Voss and Gary King) was fun. For our “Why are American Presidential election campaign polls so variable when votes are so predictable?” project a few years earlier, Gary and I had analyzed individual-level survey responses from 60 pre-election polls that had been conducted by several different polling organizations. […] The post Pre-election survey methodology: details from nine polling organizations, 1988 and 1992 appeared first on […]
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3:15 AM | One of the worst infographics ever, but people don’t care?
This post is by Phil Price. Perhaps prompted by the ALS Ice Bucket Challenge, this infographic has been making the rounds: I think this is one of the worst I have ever seen. I don’t know where it came from, so I can’t give credit/blame where it’s due. Let’s put aside the numbers themselves – […] The post One of the worst infographics ever, but people don’t care? appeared first on Statistical Modeling, Causal Inference, and Social Science.

August 27, 2014

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1:36 PM | Discussion of “A probabilistic model for the spatial distribution of party support in multiparty elections”
From 1994. I don’t have much to say about this one. The paper I was discussing (by Samuel Merrill) had already been accepted by the journal—I might even have been a referee, in which case the associate editor had decided to accept the paper over my objections—and the editor gave me the opportunity to publish […] The post Discussion of “A probabilistic model for the spatial distribution of party support in multiparty elections” appeared first on Statistical […]

August 26, 2014

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9:47 PM | Do social preferences break “I split you chose”?
Hypothesis: Social preferences undermine the fairness, efficiency, and stability of “I cut, you choose” rules. “I cut, you choose” is a method for splitting goods. It is appealing because it is easy to describe mathematically but that that doesn’t stop anyone from using it. It is a clean real world example of a classic Nash […]
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9:25 PM | Regex crossword puzzle
This showed up at the lab one day. Print it out, give it a try. I have no idea who to credit. If you don’t know what this is, that’s OK. In my opinion, ignorance, in this case, is bliss, but this explains the basic idea. And, if you’re interested, here are more puzzles.
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3:31 PM | Dave Blei course on Foundations of Graphical Models
Dave Blei writes: This course is cross listed in Computer Science and Statistics at Columbia University. It is a PhD level course about applied probabilistic modeling. Loosely, it will be similar to this course. Students should have some background in probability, college-level mathematics (calculus, linear algebra), and be comfortable with computer programming. The course is […] The post Dave Blei course on Foundations of Graphical Models appeared first on Statistical Modeling, Causal […]
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1:16 PM | Review of “Forecasting Elections”
From 1993. The topic of election forecasting sure gets a lot more attention than it used to! Here are some quotes from my review of that book by Michael Lewis-Beck and Tom Rice: Political scientists are aware that most voters are consistent in their preferences, and one can make a good guess just looking at […] The post Review of “Forecasting Elections” appeared first on Statistical Modeling, Causal Inference, and Social Science.
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7:28 AM | Pelitaito-hankkeen loppuseminaari
[Final seminar of Pelitaito project] Tiedoksi: pelikulttuuria ja pelilukutaitoa edistämään sekä pelihaittoja ennalta ehkäisemään pyrkinyt Pelitaito-projekti toteuttaa hankkeen loppuseminaarin Helsingissä 6.11.2014. Seminaari on maksuton ja paikalle mahtuu 200 ensimmäisenä ilmoittautunutta. Tässä on linkki ilmoittautumissivulle, sekä loppuseminaarin ohjelma: Good Game – Pelitaito-projektin … Continue reading → […]

August 25, 2014

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6:05 PM | Is Dog Barking the Result of Human Artificial Selection?
The Basenji also called the Congo Terrier is native to the Central African forest. Since ages he is used by the pygmies (thought to be the oldest of all humans) to hunt lions. Therefore the basenji is one of the oldest breeds of dogs. He does not bark, but he can make all the same noises that a wolf or coyote can make. He can scream, cry, howl, whine and growl.                 The... Read more
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5:36 PM | Discussion of “Maximum entropy and the nearly black object”
From 1992. It’s a discussion of a paper by Donoho, Johnstone, Hoch, and Stern. As I summarize: Under the “nearly black” model, the normal prior is terrible, the entropy prior is better and the exponential prior is slightly better still. (An even better prior distribution for the nearly black model would combine the threshold and […] The post Discussion of “Maximum entropy and the nearly black object” appeared first on Statistical Modeling, Causal Inference, […]
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2:57 PM | Cadet Impressions: Tech Entrepreneurs in Tanzania-Part 2
During our visit to Dar es Salaam, the cadets on my team, Molly Prins, Jake Moffatt, and Charlie Braman, spent time interacting with, and interviewing young tech entrepreneurs. These interviews are the raw data input for our “Developing Network Models … Continue reading →
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1:00 PM | On deck this week
Mon: Discussion of “Maximum entropy and the nearly black object” Tues: Review of “Forecasting Elections” Wed: Discussion of “A probabilistic model for the spatial distribution of party support in multiparty elections” Thurs: Pre-election survey methodology: details from nine polling organizations, 1988 and 1992 Fri: Avoiding model selection in Bayesian social research Sat, Sun: You might […] The post On deck this week appeared first on Statistical […]
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12:00 PM | Does Power Help or Hurt Perspective-Taking?
First comes love, then comes the realization that we are navigating life’s journey with another person who may have different thoughts, feelings, and beliefs than us. How do we deal with having differing viewpoints from our romantic partners? Perspective-taking is a fundamental social skill that helps us smoothly steer through the many bumps in the road, from picking out a thoughtful anniversary gift to helping us reach a compromise on a contentious issue. When people are able to consider […]
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6:06 AM | Poker math showdown!
In comments, Rick Schoenberg wrote: One thing I tried to say as politely as I could in [the book, "Probability with Texas Holdem Applications"] on p146 is that there’s a huge error in Chen and Ankenman’s “The Mathematics of Poker” which renders all the calculations and formulas in the whole last chapter wrong or meaningless […] The post Poker math showdown! appeared first on Statistical Modeling, Causal Inference, and Social Science.

August 23, 2014

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2:54 PM | How Many Mic’s Do We Rip
Yakir Reshef writes: Our technical comment on Kinney and Atwal’s paper on MIC and equitability has come out in PNAS along with their response. Similarly to Ben Murrell, who also wrote you a note when he published a technical comment on the same work, we feel that they “somewhat missed the point.” Specifically: one statistic […] The post How Many Mic’s Do We Rip appeared first on Statistical Modeling, Causal Inference, and Social Science.

August 22, 2014

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7:00 PM | Care About Health? Ditch the Bucket & Get Vaccinated
Unbeknownst to many of the public, August was National Immunization Awareness Month. I know, I know: it’s been overshadowed by some very exotic and thrilling headliners this month. The Ebola epidemic blazing defiantly in West Africa. The jaw-dropping videos shown on Discovery Channel’s “Shark Week.” The ALS Ice Bucket Challenge clogging everyone’s social feeds. Vaccines […]The post Care About Health? Ditch the Bucket & Get Vaccinated appeared first on […]
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4:24 PM | Recently in the sister blog
Meritocracy won’t happen: the problem’s with the ‘ocracy’ Does the sex of your child affect your political attitudes? More hype about political attitudes and neuroscience Modern polling needs innovation, not traditionalism Who cares about copycat pollsters? The mythical swing voter Mythical swing voter update No, all Americans are not created equal when it comes to […] The post Recently in the sister blog appeared first on Statistical Modeling, Causal Inference, […]
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1:25 PM | Replication Wiki for economics
Jan Hoeffler of the University of Gottingen writes: I have been working on a replication project funded by the Institute for New Economic Thinking during the last two years and read several of your blog posts that touched the topic. We developed a wiki website that serves as a database of empirical studies, the availability […] The post Replication Wiki for economics appeared first on Statistical Modeling, Causal Inference, and Social Science.

August 21, 2014

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1:03 PM | The field is a fractal
In a blog comment, Winston Lin points to this quote from Bill Thurston: There is a real joy in doing mathematics, in learning ways of thinking that explain and organize and simplify. One can feel this joy discovering new mathematics, rediscovering old mathematics, learning a way of thinking from a person or text, or finding […] The post The field is a fractal appeared first on Statistical Modeling, Causal Inference, and Social Science.

August 20, 2014

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1:04 PM | “A hard case for Mister P”
Kevin Van Horn sent me an email with the above title (ok, he wrote MRP, but it’s the same idea) and the following content: I’m working on a problem that at first seemed like a clear case where multilevel modeling would be useful. As I’ve dug into it I’ve found that it doesn’t quite fit […] The post “A hard case for Mister P” appeared first on Statistical Modeling, Causal Inference, and Social Science.
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4:14 AM | Big Theory
"Essentially, all models are wrong, but some are useful." --George Box*I need to be honest with you, I'm not all that good at generating novel ideas: Some of my most well-cited papers involve theories that sociologists came up with decades ago; Reviewers frequently accuse me of running post-hoc analyses (asking the data for ideas, rather than generating apriori predictions); When media cover my research, the most common initial comment is something like: "This is so obvious....blah, blah....you […]

August 19, 2014

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1:36 PM | Stroopy names
Baby Name Wizard is all over this one. And this all makes me wonder: is there a psychology researcher somewhere with a dog named Stroopy? Probably so. P.S. I just made the mistake of googling “Stroopy.” Don’t do it. I was referring to this. The post Stroopy names appeared first on Statistical Modeling, Causal Inference, and Social Science.
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12:18 PM | Working with the Disciplinarity in Game Studies
  The Summer School of Games and Play Research kicked off in Monday in Utrecht, where a large number of games scholars and students had gathered for two weeks of intensive discussions and presentations. One of the key challenges for … Continue reading →

August 18, 2014

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3:28 PM | Some quick disorganzed tips on classroom teaching
Below are a bunch of little things I typically mention at some point when I’m teaching my class on how to teach. But my new approach is to minimize lecturing, and certainly not to waste students’ time by standing in front of a group of them, telling them things they could’ve read at their own […] The post Some quick disorganzed tips on classroom teaching appeared first on Statistical Modeling, Causal Inference, and Social Science.
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