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Nathaniel Haines

@natehaines.bsky.social

800 followers 350 following 140 posts

Paid to do p(b | a) p(a) p(a | b) = ————————— p(b) Data Scientist | Computational Psychologist | Devout Bayesian https://bayesianbeginnings.com/

bayesianbeginnings.com

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Nathaniel Haines @natehaines.bsky.social · Sep 26

Using my first post to introduce myself with a Learning Bayesian Statistics podcast episode I was on recently! Come have a listen 🎧

learnbayesstats.com/episode/115-...

#115 Using Time Series to Estimate Uncertainty, with Nate Haines

Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch! My Intuitive Bayes Online Courses 1:1 Mentorship with me Our&nbs...

learnbayesstats.com

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Nathaniel Haines @natehaines.bsky.social · 10d

oops, alpha = cronbach's alpha, which is a very common measure of reliability in the psychonetric lit en.m.wikipedia.org/wiki/Cronbac...

Cronbach's alpha - Wikipedia

en.m.wikipedia.org

Nathaniel Haines @natehaines.bsky.social · 10d

because alpha is math equivalent to the average (length adjusted) split half reliability, it fits this use case well. e.g. if you score 4 of 8 items (call this test A score) and then also the left out 4 (test B score), the correlation of test A and B (across test takers) is what alpha measures

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Nathaniel Haines @natehaines.bsky.social · 10d

yeah sounds like OP is after something similar to the concept of reliability (in the psychometric sense, although not sure what the construct is here)

the whole simulation thing doesn't seem necessary if that's the case—the standard reliability measures will do

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Nathaniel Haines @natehaines.bsky.social · 22d

awesome post, and couldn't agree more with the thesis

R is great because it "just works" most of the time

Emily Riederer @emilyriederer.bsky.social · 24d

Really insightful post from Julie Tibshirani (spotted in LinkedIn, can't find on Bsky) reflecting on #rstats 's unique governance structure and what can be learned for other languages

jtibs.substack.com/p/if-all-the...

If all the world were a monorepo

The R ecosystem and the case for extreme empathy in software maintenance

jtibs.substack.com

Nathaniel Haines @natehaines.bsky.social · Aug 20

Congrats dude!!

Nathaniel Haines @natehaines.bsky.social · Aug 19

Job update! It has been a little over a month now, but I'm excited to share that I have joined Oscar Health, where I'm leading a team focused on our clinical risk adjustment process 🤓

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Nathaniel Haines @natehaines.bsky.social · Aug 8

wooahh! need to give this a read 🤓

Richard D. Morey @richarddmorey.bsky.social · Aug 8

Paper drop, for anyone interested in #metascience, #statistics, or #metaanalysis! @clintin.bsky.social and I show in a new paper in JASA that the P-curve, a popular forensic meta-analysis method, has deeply undesirable statistical properties. www.tandfonline.com/doi/full/10.... 1/?

Cover page for the manuscript: Morey, R. D., & Davis-Stober, C. P. (2025). On the poor statistical properties of the P-curve meta-analytic procedure. Journal of the American Statistical Association, 1–19. https://doi.org/10.1080/01621459.2025.2544397

Abstract for the paper: The P-curve (Simonsohn, Nelson, & Simmons, 2014; Simonsohn, Simmons, & Nelson, 2015) is a widely-used suite of meta-analytic tests advertised for detecting problems in sets of studies. They are based on nonparametric combinations of p values (e.g., Marden, 1985) across significant (p < .05) studies and are variously claimed to detect “evidential value”, “lack of evidential value”, and “left skew” in p values. We show that these tests do not have the properties ascribed to them. Moreover, they fail basic desiderata for tests, including admissibility and monotonicity. In light of these serious problems, we recommend against the use of the P-curve tests.

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Nathaniel Haines @natehaines.bsky.social · Jul 2

Ah yeah most of the work im familiar with skews toward generative models. e.g. like this classic piece, which captures various interactions between Stroop conditions, learning effects, etc.

psycnet.apa.org/record/1990-...

APA PsycNet

psycnet.apa.org

Nathaniel Haines @natehaines.bsky.social · Jul 2

Probably not what you are referring to, but the Stroop task is our main example here: psycnet.apa.org/fulltext/202...

APA PsycNet

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Nathaniel Haines @natehaines.bsky.social · Jun 27

simply amazing

Nathaniel Haines @natehaines.bsky.social · Jun 20

It has been quite a while since I posted my blog on the modeling the Dunning-Kruger effect. I intended for this to be the first of a series on modeling some classic effects in psychology/cognitive science.

Any recommendations for the second post in the series?

haines-lab.com/post/2021-01...

A Series on Building Formal Models of Classic Psychological Effects: Part 1, the Dunning-Kruger Effect | Computational Psychology

Introduction The Dunning-Kruger effect is perhaps one of the most well-known effects in all of social psychology, defined as the phenomenon wherein people with low “objective” skill tend to over-estim...

haines-lab.com

Nathaniel Haines @natehaines.bsky.social · May 13

yeah this is a great set

Nathaniel Haines @natehaines.bsky.social · May 5

Wish I could have made it in person!

Nathaniel Haines @natehaines.bsky.social · Apr 23

i have now vented on reddit and bsky so maybe i will feel better about it now

Nathaniel Haines @natehaines.bsky.social · Apr 23

last of us S2 E2, more like last episode amirite

Nathaniel Haines @natehaines.bsky.social · Apr 21

the moment some unintuitive simulation and empirical results finally click and you know what needs to be done 🤌

a feeling vibe coders can only dream of

Nathaniel Haines @natehaines.bsky.social · Apr 21

tariffs amirite

Nathaniel Haines @natehaines.bsky.social · Apr 17

Thanks for the endorsement! Awesome to hear it's been influential to your work 😁

And yes the KL finding is super interesting by itself, happy to hear someone found it buried in the supplement ha

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Nathaniel Haines @natehaines.bsky.social · Apr 17

Thank you! Glad you have found it useful 🤓

Nathaniel Haines @natehaines.bsky.social · Apr 17

it was horrible, there were 10+ papers based on the initial preprint/blog that were in print before this one eventually made it there 😅

Nathaniel Haines @natehaines.bsky.social · Apr 17

SIX YEARS after the initial blog post, this paper is finally published.. what a wild ride

- the blog: bit.ly/3GbOqQa
- original tweet thread: x.com/Nate__Haines...
- published (open access) paper: doi.org/10.1037/met0...

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Nathaniel Haines @natehaines.bsky.social · Apr 14

Yeah I've found LLM tech good for stuff that is mostly boilerplate (e.g. some general software development stuff), but when it comes to modeling work that is necessarily bespoke, they are quite bad

Nathaniel Haines @natehaines.bsky.social · Apr 12

sounds like a black mirror episode

onion person @junlper.beer · Apr 11

half of the posts on twitter remind me that the dead internet theory is very real

Nathaniel Haines @natehaines.bsky.social · Apr 11

That's called MDMA

Nathaniel Haines @natehaines.bsky.social · Apr 8

But I have not read into this lit much tbh, so I have a biased sampling of what people think 😁