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Archive of posts filed under the Decision Theory category.

Looking for rigor in all the wrong places

My talk in the upcoming conference on Inference from Non Probability Samples, 16-17 Mar in Paris: Looking for rigor in all the wrong places What do the following ideas and practices have in common: unbiased estimation, statistical significance, insistence on random sampling, and avoidance of prior information? All have been embraced as ways of enforcing […]

Stan is hiring! hiring! hiring! hiring!

[insert picture of adorable cat entwined with Stan logo] We’re hiring postdocs to do Bayesian inference. We’re hiring programmers for Stan. We’re hiring a project manager. How many people we hire depends on what gets funded. But we’re hiring a few people for sure. We want the best best people who love to collaborate, who […]

To know the past, one must first know the future: The relevance of decision-based thinking to statistical analysis

We can break up any statistical problem into three steps: 1. Design and data collection. 2. Data analysis. 3. Decision making. It’s well known that step 1 typically requires some thought of steps 2 and 3: It is only when you have a sense of what you will do with your data, that you can […]

Time Inc. stoops to the level of the American Society of Human Genetics and PPNAS?

We fiddle while Rome burns: p-value edition

Raghu Parthasarathy presents a wonderfully clear example of disastrous p-value-based reasoning that he saw in a conference presentation. Here’s Raghu: Consider, for example, some tumorous cells that we can treat with drugs 1 and 2, either alone or in combination. We can make measurements of growth under our various drug treatment conditions. Suppose our measurements […]

“Which curve fitting model should I use?”

Oswaldo Melo writes: I have learned many of curve fitting models in the past, including their technical and mathematical details. Now I have been working on real-world problems and I face a great shortcoming: which method to use. As an example, I have to predict the demand of a product. I have a time series […]

Two unrelated topics in one post: (1) Teaching useful algebra classes, and (2) doing more careful psychological measurements

Kevin Lewis and Paul Alper send me so much material, I think they need their own blogs. In the meantime, I keep posting the stuff they send me, as part of my desperate effort to empty my inbox. 1. From Lewis: “Should Students Assessed as Needing Remedial Mathematics Take College-Level Quantitative Courses Instead? A Randomized […]

Sethi on Schelling

Interesting appreciation from an economist.

“Dirty Money: The Role of Moral History in Economic Judgments”

Recently in the sister blog . . . Arber Tasimi and his coauthor write: Although traditional economic models posit that money is fungible, psychological research abounds with examples that deviate from this assumption. Across eight experiments, we provide evidence that people construe physical currency as carrying traces of its moral history. In Experiments 1 and […]

Steve Fienberg

I did not know Steve Fienberg well, but I met him several times and encountered his work on various occasions, which makes sense considering his research area was statistical modeling as applied to social science. Fienberg’s most influential work must have been his books on the analysis of categorical data, work that was ahead of […]

On deck very soon

A bunch of the 170 are still in the queue. I haven’t been adding to the scheduled posts for awhile, instead I’ve been inserting topical items from time to time—I even got some vicious hate mail for my article on the electoral college—and then I’ve been shoving material for new posts into a big file […]

An efficiency argument for post-publication review

This came up in a discussion last week: We were talking about problems with the review process in scientific journals, and a commenter suggested that prepublication review should be more rigorous: There are lot of statistical missteps you just can’t catch until you actually have the replication data in front of you to work with […]

Hark, hark! the p-value at heaven’s gate sings

Three different people pointed me to this post, in which food researcher and business school professor Brian Wansink advises Ph.D. students to “never say no”: When a research idea comes up, check it out, put some time into it and you might get some success. I like that advice and I agree with it. Or, […]

Designing an animal-like brain: black-box “deep learning algorithms” to solve problems, with an (approximately) Bayesian “consciousness” or “executive functioning organ” that attempts to make sense of all these inferences

The journal Behavioral and Brain Sciences will be publishing this paper, “Building Machines That Learn and Think Like People,” by Brenden Lake, Tomer Ullman, Joshua Tenenbaum, and Samuel Gershman. Here’s the abstract: Recent progress in artificial intelligence (AI) has renewed interest in building systems that learn and think like people. Many advances have come from […]

The social world is (in many ways) continuous but people’s mental models of the world are Boolean

Raghu Parthasarathy points me to this post and writes: I wrote after seeing one too many talks in which someone bases boolean statements about effects “existing” or “not existing” (infuriating in itself) based on “p < 0.05” or “p > 0.5”. Of course, you’ve written tons of great things on the pitfalls, errors, and general […]

How to think about the p-value from a randomized test?

Roahn Wynart asks: Scenario: I collect a lot of data for a complex psychology experiment. I put all the raw data into a computer. I program the computer to do 100 statistical tests. I assign each statistical test to a key on my keyboard. However, I do NOT execute the statistical test. Each key will […]

“So such markets were, and perhaps are, subject to bias from deep pocketed people who may be expressing preference more than actual expectation”

Geoff Buchan writes in with another theory about how prediction markets can go wrong: I did want to mention one fascinating datum on Brexit: one UK bookmaker said they received about twice as many bets on leave as on remain, but the average bet on remain was *five* times what was bet on leave, meaning […]

Using Stan in an agent-based model: Simulation suggests that a market could be useful for building public consensus on climate change

Jonathan Gilligan writes: I’m writing to let you know about a preprint that uses Stan in what I think is a novel manner: Two graduate students and I developed an agent-based simulation of a prediction market for climate, in which traders buy and sell securities that are essentially bets on what the global average temperature […]

Frustration with published results that can’t be reproduced, and journals that don’t seem to care

Thomas Heister writes: Your recent post about Per Pettersson-Lidbom frustrations in reproducing study results reminded me of our own recent experience that we had in replicating a paper in PLOSone. We found numerous substantial errors but eventually gave up as, frustratingly, the time and effort didn’t seem to change anything and the journal’s editors quite […]

“A bug in fMRI software could invalidate 15 years of brain research”

About 50 people pointed me to this press release or the underlying PPNAS research article, “Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates,” by Anders Eklund, Thomas Nichols, and Hans Knutsson, who write: Functional MRI (fMRI) is 25 years old, yet surprisingly its most common statistical methods have not been validated […]