Peder M Isager

Indeed, I'm looking forward!

Extremely honored to recieve Oslo New University College's science award for 2025. ONH has been a fantastic base to conduct my research at for the past 4 years, and I have an amazing team of colleagues around me to thank for that. From the bottom of my heart, thank you all!

Okay everyone, things are getting serious. I’m going to teach research methods again, 1st year psychology undergraduates. What would you cover with respects to philosophy of science, the research process etc.? I’m not very happy with the textbook stuff so I’m open to all ideas!

True, and maybe that should be emphasized in the blog post. Will consider adding a section at the end of the post. Any sources you'd recommend I'd cite in a section like this?

An abbreviation (ABB) in a journal article (JA) or Grant Application (GA) is rarely worth the words it saves. Every ABB requires cognitive resources (CR) and at my age by the time I'm halfway through a JA or GA I no longer have the CR to remember what your ABB stood for.

To be clear, the point of this post is not to say only experiments support causal inference and correlational research never can. Quite the opposite in fact. If that was your takeaway, I may need to add some language to clarify.

The motivation for picking the example in this post was simply that I wanted a thought experiment that a 1st year undergraduate in most areas of social and health science could wrap their head around without any additional reading.

I actually use the history of smoking~cancer research as my running example when introducing our bachelor students to research design and experimental vs observational research. It's a terrific example, albeit on a tragic subject.

Yes, one of several practical problems. You have to assume a perfect implementation for the hypothesis diagram to be true without caveats. Still, coming from a field where none of this is made explicit in most textbooks, I think understanding the unrealistically perfect case can be helpful.

Given that I wanted to cap the post at ~1000 words a lot of nuance will obviously be lost. Still, I think this post provides a useful preface to a proper causal inference introduction like Pearl's primer book.

Thanks for the reference, will check this out! I absolutely agree, and I don't think I say anything of the sort. However, I wanted to write a post that in very simple terms lays out the causal graphical logic underlying the textbook statement "you have to use experiments to make causal claims".

Later on the authors recommend abductive inference. I agree with the recommendation. However, abduction that leads us to a causal conclusion is just causal inference by another name. Saying that causal inference is not allowed is not sage advice. Better to emphasize that causal inference is hard.

I understand that sensible causal inference based on (cross-sectional) correlations can be hard. Very hard. But that does not mean our goal should not be causal inference. If a network modeling approach invalidates any causal inference, I question the usefulness of such a modeling approach.

Can we infer causal relations from undirected network models of mental disorders? Some authors apparently say no. Personally, I don't see what network models are good for if they can't help us understand disease etiology (i.e. causality).

Quote from onlinelibrary.wiley.com/doi/10.1002/...

Absolutely, feel free!

I mean, randomized control is usually mentioned in any explanation, but why is randomization to begin with? Why does randomization and manipulation give experiments a leg up on observational research when it comes to causal inference? This blog post is an attempt to explain why, briefly.

New blog post! Why experiments are the gold standard for answering causal questions (pedermisager.org/blog/why-exp...). Many text books insist on experimental evidence to draw causal inferences bvut don't fully explain exactly what gives experiments their special powers.

The idea that if you're a poor researcher you should automatically be assigned to teach instead makes about as much sense as the idea that if you're a poor teacher you should automatically be assigned to do research instead.

"Those who cannot do, teach" is, I think, another sacred cow of academia. "Those who cannot teach, do" strikes me as equally true. A good teacher seems more valuable to the academy than a good researcher, on average.

RE @nulliusinverba.bsky.social ep 59: Meehl seems to assume that research is harder than teaching; teachers should be paid less and if you can't do interesting research you're "demoted" to teaching. Why not the opposite? Why not pay teachers more and say "if you cannot teach, do"?

YouTube video by Numberphile The Feigenbaum Constant (4.669) - Numberphile

Currently on chapter 2 "Chaos and unpredictability". Before reading this chapter, I highly recommend watching this Numberphile's video (www.youtube.com/watch?v=ETrY...) which is a neat little introduction to chaos, and is really helpful for developing an intuition about bifurcation plots.

Currently reading "Complex Systems Research in Psychology" (santafeinstitute.github.io/ComplexPsych/). If you're interested systems psychology/psychopathology, give this a read. van der Maas gives a very broad introduction to the topic, and supplements text with R code and practical exercises.

I often talk about the need for psychology to improve. That is because I think it is worth improving. It would be very helpful if I could easily provide a few dozen examples of the contributions that have been made to support that conviction. I know they exist. I would just like them in one place.

Just discovered "Mental health professionals’ attitudes towards the network theory of mental disorders" by @leahschumaker.bsky.social & Levente Kriston (osf.io/462cs). Fascinating read. Partly confirms suspicion I've had for a while that therapists see NTMD as "nothing new" (but see pub for details)

My editorial on how journals can earn trust.

We often use journal names as proxies for quality. This is bad bc it’s not valid. But it could be. Editors could make journal name a valid signal. And we could place value on journals that show us how they do that.

journals.sagepub.com/doi/full/10....

There is still time to sign up for the last workshop of this academic year at PMGS, "Scientific Criticism and Peer Review," by @renebekkers.mastodon.social.ap.brid.gy
Check out the details here:
paulmeehlschool.github.io/workshops/cr...

Psych-DS is (1) spellcheck for your datasets and (2) a pathway to standardizing data in our academic fields that *everyone* can learn.

And it's live RIGHT NOW!

psych-ds.github.io

(This is the announcement post I've been leading up to)

I'll finally get to teach a workshop on one of my favourite subjects - causal inference - at the Paul Meehl graduate school may 9th! Ever wondered what the point is of controlling for variables in your regression analysis? Come find out with us!

New workshop announced: Causal Inference and Variable Control | Paul meehl Graduate School We are excited to announce that registration is now open for the workshop “Causal Inference and Variable Control”. In this...

The new workshop of Paul Meehl Graduate School, Causal Inference and Variable Control by @isager.bsky.social, is open for registration. Check out the announcement below:
paulmeehlschool.github.io/2025-04-02-c...

Looking for a PhD/Postdoc in Switzerland? English speaking lab, good pay, incredible scenery.

There's lots of funding calls for projects related to my work on the meta-science of measurement, error detection and trustworthiness assessment. Reach out if you're interested in writing a grant together.