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Archive of posts filed under the Decision Theory category.

Still cited only 3 times

I had occasion to refer to this post from a couple years ago on the anthropic principle in statistics. In that post, I wrote: I actually used the anthropic principle in my 2000 article, Should we take measurements at an intermediate design point? (a paper that I love; but I just looked it up and […]

She’s thinking of buying a house, but it has a high radon measurement. What should she do?

Someone wrote in with a question: My Mom, who has health issues, is about to close on a new house in **, NJ. We just saw that ** generally is listed as an area with high radon. If the house has a radon measurement over 4 and the seller puts vents to bring it into […]

Evidence-based medicine eats itself in real time

Robert Matthews writes:

“Prediction Markets in a Polarized Society”

Rajiv Sethi writes about some weird things in election prediction markets, such as Donald Trump being given a one-in-eight chance of being the election winner . . . weeks after he’d lost the election. Sethi writes: There’s a position size limit of $850 dollars per contract in this market, which also happens to have hit […]

Open data and quality: two orthogonal factors of a study

It’s good for a study to have open data, and it’s good for the study to be high quality. If for simplicity we dichotomize these variables, we can find lots of examples in all four quadrants: – Unavailable data, low quality: The notorious ESP paper from 2011 and tons of papers published during that era […]

Call for a moratorium on the use of the term “prisoner’s dilemma”

Palko writes: I’m not sure what the best way to get the ball rolling here would be (perhaps a kickstarter?) but we need to have a strictly enforced rule that no journalist or pundit is allowed to mention the prisoner’s dilemma for the next five or ten years, however long it takes to learn to […]

Which sorts of posts get more blog comments?

Paul Alper writes: Some of your blog postings elicit many responses and some, rather few. Have you ever thought of displaying some sort of statistical graph illustrating the years of data? For example, sports vs. politics, or responses for one year vs. another (time series), winter vs. summer, highly technical vs. breezy. I’ve not done […]

More on that credulity thing

I see five problems here that together form a feedback loop with bad consequences. Here are the problems: 1. Irrelevant or misunderstood statistical or econometric theory 2. Poorly-executed research 3. Other people in the field being loath to criticize, taking published or even preprinted claims as correct until proved otherwise 4. Journalists taking published or […]

Epistemic and aleatoric uncertainty

There was some discussion in comments recently about the distinction between aleatoric uncertainty (physical probabilities such as coin flips) and epistemic uncertainty (representing ignorance rather than an active probability model). We’ve talked about this before, but not everyone was reading this blog 15 years ago, so I’ll cover it again here. For a very similar […]

Confidence intervals, compatability intervals, uncertainty intervals

“Communicating uncertainty is not just about recognizing its existence; it is also about placing that uncertainty within a larger web of conditional probability statements. . . . No model can include all such factors, thus all forecasts are conditional.” — us (2020). A couple years ago Sander Greenland and I published a discussion about renaming […]

Many years ago, when he was a baby economist . . .

Jonathan Falk writes: Many years ago, when I was a baby economist, a fight broke out in my firm between two economists. There was a question as to whether a particular change in the telecommunications laws had spurred productivity improvements or not. There a trend of x% per year in productivity improvements that had gone […]

Instead of comparing two posterior distributions, just fit one model including both possible explanations of the data.

Gabriel Weindel writes: I am a PhD student in psychology and I have a question about Bayesian statistics. I want to compare two posterior distributions of parameters estimated from a (hierarchical) cognitive model fitted on two dependent variables (hence both fits are completely separated). One fit is from a DV allegedly containing psychological process X […]

Here is how you should title the next book you write.

I was talking with someone about book titles. I thought Red State Blue State Rich State Poor State was a good title, but the book did not sell as well as I hoped (not that I thought it would sell enough to make me lots of money; I’m just using sales here as a proxy […]

Statisticians don’t use statistical evidence to decide what statistical methods to use. Also, The Way of the Physicist.

David Bailey, a physicist at the University of Toronto, writes: I thought you’d be pleased to hear that a student in our Advanced Physics Lab spontaneously used Stan to analyze data with significant uncertainties in both x and y. We’d normally expect students to use python and orthogonal distance regression, and STAN is never mentioned […]

Is the right brain hemisphere more analog and Bayesian?

Oliver Schultheiss writes: I recently commented one of your posts (I forgot which one) with a reference to evidence suggesting that the right brain hemisphere may be in a better position to handle numbers and probabilistic predictions. Yesterday I came across the attached paper by Filipowicz, Anderson, & Danckert (2016) that may be of some […]

“Our underpowered trial provides no indication that X has a positive or negative effect on Y”

It’s rare to see researchers say flat-out that an experimental result leaves them uncertain. There seems to be such a temptation to either declare victory with statistical significance (setting the significance level to 0.1 if necessary to clear the bar) or to claim that weak and noisy results are “suggestive” or, conversely, to declare non-significance […]

“Small Steps to Accuracy: Incremental Updaters are Better Forecasters”

Pavel Atanasov writes: I noticed your 2016 post on belief updating. Here is the key bit: From the perspective of the judgment and decision making literature, the challenge is integrating new information at the appropriate rate: not so fast that your predictions jump up and down like a yo-yo (the fate of naive poll-watchers) and […]

Hierarchical stacking, part II: Voting and model averaging

(This post is by Yuling) Yesterday I have advertised our new preprint on hierarchical stacking. Apart from the methodology development, perhaps I could draw some of your attention to the analogy between model averaging/selection and voting systems. Model selection = we have multiple models to fit the data and we choose the best candidate model. Model […]

My reply: Three words. Fake. Data. Simulation.

Kash Ramli writes: I am planning on running an experiment to determine whether an adaptive treatment approach to behaviour change interventions could be effective at reducing the heterogenous treatment effects currently observed in the field. The context of the experiment is providing households with social norms based feedback of their consumption (i.e. comparing your consumption […]

What about that new paper estimating the effects of lockdowns etc?

A couple people pointed me to this article, “Assessing Mandatory Stay‐at‐Home and Business Closure Effects on the Spread of COVID‐19,” which reports: The most restrictive non‐pharmaceutical interventions (NPIs) for controlling the spread of COVID‐19 are mandatory stay‐at‐home and business closures. . . . We evaluate the effects on epidemic case growth of more restrictive NPIs […]