Martin Modrák
@modrakm.bsky.social
1.2K followers 36 following 150 posts
Biostatistics/bioinformatics at Charles University, 2nd faculty of Medicine. Bayesian in practice, but not a fan of Bayesian epistemology. Main on fedi: https://bayes.club/@modrak_m Blog: https://martinmodrak.cz
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If you feel so inclined, I run a Mastodon instance bayes.club and try to make it a nice place and you can join if you like. I know some people have strong opinions on this and some have had bad experience on Mastodon. And that's all fair and I won't dispute that, there's a lot of work to do.
Bayes Club
A community of statisticians using Bayesian methods.
bayes.club
Reposted by Martin Modrák
Nobody:
Line plots: These are her mountains and skies and she radiates
Through history's rivers of blood, she regenerates
Reposted by Martin Modrák
richarddmorey.bsky.social
One thing I find so strange about the P-curve is how once it was published, the burden of proof shifted to others to prove that it is bad (in ways that Simonsohn would care about, at least), rather than the authors, to prove that it works in general (for standard definitions of "works"). (21/x)
Reposted by Martin Modrák
richarddmorey.bsky.social
Simonsohn has now posted a blog response to our recent paper about the poor statistical properties of the P curve. @clintin.bsky.social and I are finishing up a less-technical paper that will serve as a response. But I wanted to address a meta-issue *around* this that may clarify some things. 1/x
datacolada.bsky.social
Would p-curve work if you dropped a piano on it?
datacolada.org/129
PIano being dropped on car in car testing facility
Reposted by Martin Modrák
jbakcoleman.bsky.social
It's officially been a year since this paper was retracted. In the wake, the authors claimed (misleadingly) it was just a couple pesky sentences... a revise and resubmit.

Since then, radio silence with not even an update to the preprint.

www.nature.com/articles/s41...
Retraction Note: High replicability of newly discovered social-behavioural findings is achievable - Nature Human Behaviour
Nature Human Behaviour - Retraction Note: High replicability of newly discovered social-behavioural findings is achievable
www.nature.com
Fewer people hit/spank/beat their kids and it is less socially acceptable to do so.
Reposted by Martin Modrák
mareike.bsky.social
this might be a bit of a long shot, but is anyone here willing to share documents of an ERC (starting) grant? or any insights into the process, things you wished you knew before…? i would be very thankful as i think it is quite different from programs i am familiar with so far. ☀️
But apparently most of the Internet agrees that "population" estimates are "preferred for RCTs" but without any explanation why! Have I lost my mind? Or is this one of the situation where "we have always done things this way"? 3/3
they worry that for one outcome GLMMs provide "subject-specific" estimate and we should consider GEE to get "population" estimate. This seems weird to me, because the sites are a convenience sample and I really want to generalize to other sites and make decisions for individual patients 2/3
I am **NOW** writing a response to regulator on a first RCT I helped design and the plan is to use random intercepts for sites, so I ponder as well. The regulator doesn't mind the random effects (we plan fixed ef as sensitivity analysis), but, on a related note, 1/3
Reposted by Martin Modrák
techconnectify.bsky.social
*cracks knuckles*

okay so you know how the media has a problem with taking snippets of scientific studies out of context and writing articles which mislead the public?

now imagine a computer program is doing that when you ask it questions about scientific literature but also it makes stuff up.
Reposted by Martin Modrák
avehtari.bsky.social
Stan / CmdStan 2.37 release!
blog.mc-stan.org/2025/09/02/r...
- sum_to_zero_matrix type sums to zero across both rows and columns
- simplex and *_stochastic_matrix types should be now faster and more stable
- new functions exposing the built-in constraint implementations
1/2
Release of CmdStan 2.37
We are very happy to announce that the 2.37.0 release of CmdStan is now available on Github! As usual, the release of CmdStan is accompanied by new releases of Stan Math, core Stan, and Stanc3. Thi…
blog.mc-stan.org
Reposted by Martin Modrák
healthstatsdude.bsky.social
A SQL query goes into a bar, walks up to 2 tables and says “Can I join you?”
Obligatory: xkcd.com/978/
The LLM use could however increase efficiency of the process substantially
Citogenesis
xkcd.com
Reposted by Martin Modrák
dlgenealogist.bsky.social
Destroy this myth. Please share if you have visited and researched in a library this past year! RT And give a shout out to your favorite library you have ever visited.
Reposted by Martin Modrák
hggaddy.bsky.social
📢 Interested in excess mortality methods, and want a challenge? I'm organising the "One Epidemic, Many Estimates" (1EME) project! Register *now* as a many analyst team (submissions due 15 March 2026), and then join us at LSE for a workshop on 21-22 May 2026! (1/n)

www.lse.ac.uk/Economic-His...
One Epidemic, Many Estimates (1EME)
One Epidemic, Many Estimates (1EME)
www.lse.ac.uk
Reposted by Martin Modrák
pengzell.bsky.social
Great to see this happen and a good opportunity to caution against some pitfalls in many-analyst studies: www.pnas.org/doi/10.1073/...

Can't imagine a better team to pull this off, so do join
hggaddy.bsky.social
📢 Interested in excess mortality methods, and want a challenge? I'm organising the "One Epidemic, Many Estimates" (1EME) project! Register *now* as a many analyst team (submissions due 15 March 2026), and then join us at LSE for a workshop on 21-22 May 2026! (1/n)

www.lse.ac.uk/Economic-His...
One Epidemic, Many Estimates (1EME)
One Epidemic, Many Estimates (1EME)
www.lse.ac.uk
Reposted by Martin Modrák
dingdingpeng.the100.ci
Ever stared at a table of regression coefficients & wondered what you're doing with your life?

Very excited to share this gentle introduction to another way of making sense of statistical models (w @vincentab.bsky.social)
Preprint: doi.org/10.31234/osf...
Website: j-rohrer.github.io/marginal-psy...
Models as Prediction Machines: How to Convert Confusing Coefficients into Clear Quantities

Abstract
Psychological researchers usually make sense of regression models by interpreting coefficient estimates directly. This works well enough for simple linear models, but is more challenging for more complex models with, for example, categorical variables, interactions, non-linearities, and hierarchical structures. Here, we introduce an alternative approach to making sense of statistical models. The central idea is to abstract away from the mechanics of estimation, and to treat models as “counterfactual prediction machines,” which are subsequently queried to estimate quantities and conduct tests that matter substantively. This workflow is model-agnostic; it can be applied in a consistent fashion to draw causal or descriptive inference from a wide range of models. We illustrate how to implement this workflow with the marginaleffects package, which supports over 100 different classes of models in R and Python, and present two worked examples. These examples show how the workflow can be applied across designs (e.g., observational study, randomized experiment) to answer different research questions (e.g., associations, causal effects, effect heterogeneity) while facing various challenges (e.g., controlling for confounders in a flexible manner, modelling ordinal outcomes, and interpreting non-linear models).
Figure illustrating model predictions. On the X-axis the predictor, annual gross income in Euro. On the Y-axis the outcome, predicted life satisfaction. A solid line marks the curve of predictions on which individual data points are marked as model-implied outcomes at incomes of interest. Comparing two such predictions gives us a comparison. We can also fit a tangent to the line of predictions, which illustrates the slope at any given point of the curve. A figure illustrating various ways to include age as a predictor in a model. On the x-axis age (predictor), on the y-axis the outcome (model-implied importance of friends, including confidence intervals).

Illustrated are 
1. age as a categorical predictor, resultings in the predictions bouncing around a lot with wide confidence intervals
2. age as a linear predictor, which forces a straight line through the data points that has a very tight confidence band and
3. age splines, which lies somewhere in between as it smoothly follows the data but has more uncertainty than the straight line.
Reposted by Martin Modrák
news.rte.ie
Israeli strikes on Nasser Hospital in Gaza this morning have killed at least 15 people, including three journalists, one of whom worked for Reuters and one who worked for Al Jazeera
Israel hits Gaza hospital, killing at least 15 people
Israeli strikes on Nasser Hospital in Gaza this morning have killed at least 15 people, including three journalists, one of whom worked for Reuters and one who worked for Al Jazeera.
www.rte.ie
+1 I rarely get much stuff done when caring for the kids, except when the dishwasher needs unloading :-D
Reposted by Martin Modrák
clintin.bsky.social
New paper with @richarddmorey.bsky.social now out in JASA, where we critically examine p-curve. Below is Richard’s excellent summary of the many poor statistical properties of p-curve (with link to paper). I wanted to add some conceptual issues that we also tackle in the paper.
richarddmorey.bsky.social
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.
Reposted by Martin Modrák
richarddmorey.bsky.social
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.
My experience also supports that. The workout/exercise stuff was explained to a hopeless ~22yo me by a friend and he was right: the effects of workout on your mental state and relationship to your body are both more important and easier to achieve than any noticeable change in your appearance.