Matti Vuorre
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matti.vuorre.com
Matti Vuorre
@matti.vuorre.com

I am an assistant professor at the department of Social Psychology at Tilburg University's School of Social and Behavioral Sciences.

I have a website at https://vuorre.com.

All posts are posts.

Psychology 44%
Neuroscience 13%
Pinned
I am hiring PhD candidates to study the psychology of attention & technology use at @tilburg-university.bsky.social.

We're looking for motivated & curious scholars with expertise in cognitive psychology and statistics, and offer a friendly work environment with great terms & benefits.

tiu.nu/22989

And that's a fine conclusion too (if we can be confident in it) and should directly inform the next experiment (probably need way more participants then.)

Thanks, interesting paper. I'm missing a conclusion in the example write-up. Is it that the hypotheses (JND & prior SD) are so uncertain that there cannot be a conclusion? I find this generally the stickiest point against interval tests.

4 of 17 member institutions are in the Netherlands 🇳🇱
PsyArXiv is pleased to welcome new member institutions!
✨Eindhoven University of Technology
✨New York University
✨Tilburg University
✨University College London

Member institutions are integral to helping PsyArXiv deliver preprint posting and reading to its users at no charge.
PsyArXiv is pleased to welcome new member institutions!
✨Eindhoven University of Technology
✨New York University
✨Tilburg University
✨University College London

Member institutions are integral to helping PsyArXiv deliver preprint posting and reading to its users at no charge.

I am not averse to the S value, and I like how it converts the question to one of quantifying information. It would be lovely to see some experiments evaluating whether it could deliver (so comparing interpretations & decisions against p values etc.)

Looks great, I'll read tmrw. I am not sure what the panda thing is though! avi why not use a more modern video codec

😢

Who said stats is hard!

I just encountered this for the first time last week: I could view but not download a paper. wtf
Now this is a new one: My university's license of SAGE journals allows me to view but not to download the research articles. According to ChatGPT read-access costs 100K€ p.a. If you want to make 100% sure that interested readers can access your article, publish it in a #diamondopenaccess journal.

So if I flip it I can then say null is equally probable as x *tails* in a row 🥴

If the null is true these results (or more extreme) have the same surprisal value as x heads in a row? Am I reading this right?
A colleague is looking for an open-source/online (pref. peer-reviewed) reference for properties of probability distributions. Any ideas? (NIST gives *very* basic properties e.g. www.itl.nist.gov/div898/handb... but I think they're looking for something more complete ...)

Reposted by Matti Vuorre

Now this is a new one: My university's license of SAGE journals allows me to view but not to download the research articles. According to ChatGPT read-access costs 100K€ p.a. If you want to make 100% sure that interested readers can access your article, publish it in a #diamondopenaccess journal.
🚨 New draft 🚨

We built an LLM-enabled system to measure greenwashing scores in 1 million worldwide Facebook ads.

We found vast networks of Facebook pages sharing pro-fossil fuel messages & show that ads are targeted at left-leaning areas with fossil fuel investments.

Link: doi.org/10.48550/arX...

The MSFT angry bird 🫡

It's always sunny in philadelphia.

Microdosing hot peppers! We need more science on this asap.
two police officers shake hands in front of a sign that says fx
ALT: two police officers shake hands in front of a sign that says fx
media.tenor.com

For anyone who hasn't seen it yet, season 17 was very good. It brought back a lot of the elements from earlier seasons that made the show what it is (though not all the minor characters I'd have hoped for). I also appreciate the 8 episodes per season format--quality over quantity.

Incredible dataviz.
Time for another episode of “bad data viz”

This one truly has me here thinking “Am I a Dolt?” What is this even saying??? Doesn’t WSJ have amazing talented staff skilled in data visualization? Like.. what is this?

Reposted by Matti Vuorre

Time for another episode of “bad data viz”

This one truly has me here thinking “Am I a Dolt?” What is this even saying??? Doesn’t WSJ have amazing talented staff skilled in data visualization? Like.. what is this?

Reposted by Matti Vuorre

It's easy to produce spurious findings:
A meaningless score based on irrelevant evaluations (“My relationship has very good Saturn”) was moderately related to common relationship measures (satisfaction, commitment) & predicted those measures 3 weeks later

journals.sagepub.com/doi/10.1177/...

So 'working on files on my computer' <-> syncing with a cloud system (github et al.) -> archiving the files and directories (zenodo et al). It's not rocket science!

I agree. This might have something to do with supporting "modular" research projects / publishing, but at the very least the UI does not help. I support using something called a 'file system' where projects can have 'directories' and 'files', and those can be easily shared & collaborated on :)

This post highlights how far behind the OSF is in usability and speed. The ResearchBox UI does seem clean, but why not use Zenodo directly (RB archives to Zenodo anyway.)

Thanks!

Time to stop doing non-open reviews or at least complain to the journal? That sucks.

How strong is strong? Posteriors for 50% n=2,4,8,16 plz 🙏

Yeah makes sense. Also probably 'sensitive' behaviors affected differently / for longer time. What if I just never tell the participants 🥸

This episode reminded me of 2 things:

1. We know how & why the bootstrap works, but the fact that it does is just very cool.
2. Bayes. All that strapping (& which bias adjustment to choose) just goes away as unnecessary.
Join us tomorrow as we repeat ourselves.
Join us as we repeat ourselves tomorrow.
Tomorrow, we repeat ourselves. Join us!