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Manjari Narayan | @Neurostats

@neurostats.org

7.3K followers 860 following 1.6K posts

AI in Bio & Health & Therapeutic Development Bio: https://linktr.ee/mnarayan Substack: https://blog.neurostats.org Peek into my brain: notes.manjarinarayan.org Previously @dynotx @StanfordMed PhD@RiceU_ECE | BS@ECEILLINOIS 🧪🧮⚕️🧬🧠🖥🤖📈✍️🩺👩‍📈📉

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Manjari Narayan | @Neurostats @neurostats.org · Jan 7

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Folks are asking for resources for learning about causal inference.
Here is a comprehensive reading list since no one address all issues —
What is causality?
When is a causal relationship is knowable?
How to infer causal relationships given from noisy and limited data?

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Reposted by Manjari Narayan | @Neurostats

Peter Tennant @pwgtennant.bsky.social · Jul 17

I think the problem here is that most people who do epidemiological research - including many who might call themselves 'epidemiologists' - have not actually had any epidemiology training. I wish it was a protected title. With an exam that would require proving you understand residual confounding!

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Manjari Narayan | @Neurostats @neurostats.org · Jul 17

Otherwise, I'm more considered about pre-validation issues — correcting for chronological age without nested cross-validation in biomarker prediction models.

The nonlinear thing becomes an issue if you want to make a claim that residuals are independent of age.

Reposted by Manjari Narayan | @Neurostats

Thomas Dietterich @tdietterich.bsky.social · Jun 26

For example, current evidence is that LLMs rely too much on interpolation rather than discovering underlying invariant causal abstractions.

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Manjari Narayan | @Neurostats @neurostats.org · Jun 27

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Manjari Narayan | @Neurostats @neurostats.org · Jun 27

Same goes for structure determines function concepts

Manjari Narayan | @Neurostats @neurostats.org · Jun 27

I think Cox is earnest. It is scary to listen to him because he is right that the AI presentation of "facts" is largely based on what is popular, but you can also steer it to selectively give you evidence that confirms your own worldview.

Manjari Narayan | @Neurostats @neurostats.org · Jun 27

This appears to be a very problematic weaponization of casual reasoning that feels 'rigorous' because it involves a selective presentation of evidence. Some very excellent researchers have looked into the problems from air pollution.

#CausalSky #MetaSky

www.theguardian.com/technology/n...

Inside a plan to use AI to amplify doubts about the dangers of pollutants

Risk analyst Tony Cox’s work has been backed by the chemical lobby, and some health experts are alarmed

www.theguardian.com

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Manjari Narayan | @Neurostats @neurostats.org · Jun 25

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Manjari Narayan | @Neurostats @neurostats.org · Jun 22

What year was this picture taken in?

Manjari Narayan | @Neurostats @neurostats.org · Jun 22

Exactly

> The people who care about a topic enough to research it will often have ideological motivations. The ideological influence is there. That doesn’t mean it’s bad science.

Andrew Gelman et al. @statmodeling.bsky.social · Jun 20

NIH plan to remove ideological influence from science. How does this fit in the junk science being promoted by the U.S. Dept of Health and Human Services?
statmodeling.stat.columbia.edu/2025/06/20/n...

NIH plan to remove ideological influence from science. How does this fit in the junk science being promoted by the U.S. Dept of Health and Human Services? | Statistical Modeling, Causal Inference, a...

statmodeling.stat.columbia.edu

Manjari Narayan | @Neurostats @neurostats.org · Jun 22

Every few years there is a new article like this, but not much will change unless scientists stop relying on GraphPad Prism that doesn't offer any of this and have something they can use more easily.

LLM powered workflows might change this going forward.

Jason Moore @moorejh.bsky.social · Jun 22

A brief guide to statistical analysis of grouped data in preclinical research www.nature.com/articles/s42... #datascience #bioinformatics #statistics #mlsky

A brief guide to statistical analysis of grouped data in preclinical research - Nature Metabolism

Clustering and nesting (C&N) arise in many preclinical studies, such as when animals are group-housed or share litters, or in cell culture. Ignoring C&N undermines the validity of analyses. He...

www.nature.com

Manjari Narayan | @Neurostats @neurostats.org · Jun 22

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Manjari Narayan | @Neurostats @neurostats.org · Jun 21

The grass is not greener, I'm afraid.

Manjari Narayan | @Neurostats @neurostats.org · Jun 21

It's a niche for sure. But it exists and it's underutilized and could be further developed

Manjari Narayan | @Neurostats @neurostats.org · Jun 21

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Manjari Narayan | @Neurostats @neurostats.org · Jun 21

Unless you are using inferential clustering methods that are designed to severely test any hypotheses against the baseline that "how often would you find clusters if the data was generated by these high dimensional null patterns or if data were corrupted by structured measurement error"

Kevin M. King @kevinmking.bsky.social · Jun 20

1) LCAs are designed to find classes. So when a paper's Aim I is "We'll use LCA to see if there are classes", it's like saying "We're going to estimate a mean and see if there's an SD". It's that dumb

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Manjari Narayan | @Neurostats @neurostats.org · Jun 21

Can you demonstrate the extent and degree of different kinds of sequential selection biases from a #CausalSky #StatSky #MedSky perspective in public clinical trial datasets?

DM me if you are interested.

For instance in TrialBench?
github.com/ML2Health/ML...

ML2ClinicalTrials/Trialbench at main · ML2Health/ML2ClinicalTrials

Contribute to ML2Health/ML2ClinicalTrials development by creating an account on GitHub.

github.com

Reposted by Manjari Narayan | @Neurostats

Evgeni V Pavlov @evgenivpavlov.bsky.social · Jun 20

She wrote this in May…

Can’t take it with you

I am in hospice care and reflecting a lot on what a good life is.

open.substack.com

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Reposted by Manjari Narayan | @Neurostats

Marco A. Maximo Prado @maximoprado.bsky.social · Jun 20

the Mesoscopic Integrated Neuroimaging Data (MIND) platform will soon be opening also for outside researchers leveraging our new 15.2 T 🐁 MRI, SHIELD clearing and fully upgraded lightsheet microscope plus computational resources developed by @neuroak.bsky.social to handle large datasets.

Marco A. Maximo Prado @maximoprado.bsky.social · Jun 20

Great news just announced. @neuroak.bsky.social is leading a new funded @braincanada.bsky.social platform that promises to revolutionize the study of neurodegeneration by tackling Patho-connectomics Merging MRI and lightsheet analysis in new models of disease www.schulich.uwo.ca/about/news-e...

Researchers launch brain imaging platform with $2.9M boost from Brain Canada - Schulich School of Medicine & Dentistry - Western University

A new high-resolution imaging platform is revealing the brain in extraordinary detail – and sharing the data with scientists worldwide.

www.schulich.uwo.ca

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Manjari Narayan | @Neurostats @neurostats.org · Jun 20

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Manjari Narayan | @Neurostats @neurostats.org · Jun 20

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Manjari Narayan | @Neurostats @neurostats.org · Jun 19

I also think most of the authors were not solid neuroimaging researchers. It was like a fun project. Not particularly good science.

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Manjari Narayan | @Neurostats @neurostats.org · Jun 19

Neurobullshit is alive and well in education research. Reminds me of the good old days of @neuroskeptic.bsky.social on this 10+ years ago

Dr Abeba Birhane @abeba.bsky.social · Jun 19

I think the conclusion of this study is likely to be valid however it is worth noting that any attempts to localise cognitive tasks such as writing to a specific brain activation/connectivity is problematic because that's not how the brain works.

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Manjari Narayan | @Neurostats @neurostats.org · Jun 18

substack.com/@manjarinara...

Manjari Narayan on Substack

The part Box said that is often left out. “The practical question is how wrong do (models) have to be to not be useful.”

substack.com

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Manjari Narayan | @Neurostats @neurostats.org · Jun 18

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