Tobias Fellinger

Causal clarity in statistical software Imagine running a simple regression in any statistical software of choice—but this time, you only get a point estimate of the regression coefficient. There

Should statistical software that estimates causal effects also tell you the causal assumptions under which that estimate can be interpreted as causal?

I don't know but my PhD student Maurice Korf has some thoughts (and software) to get the conversation going:

academic.oup.com/ije/article/...

29.07.2025 07:47 — 👍 53    🔁 15    💬 3    📌 0

The distinction between causal, predictive, and descriptive research—there is still room for improvement It has been proposed that medical research questions can be categorised into three classes: causal, predictive, and descriptive. This distinction was proposed to encourage researchers to think clearly...

The distinction between causal, predictive, and descriptive research—there is still room for improvement - Journal of Clinical Epidemiology www.jclinepi.com/article/S089...

18.09.2025 19:29 — 👍 10    🔁 3    💬 1    📌 0

Great experience with a novel format of an invited session of #stratos TG2 @biometricsociety.bsky.social Austro-Swiss region meeting (ROeS 2025 Graz) (1/n)

18.09.2025 17:43 — 👍 4    🔁 2    💬 1    📌 0

Thanks to all co-authors!

(Of who only @poschm.bsky.social is present on bluesky If I'm not mistaken.)

20.02.2025 14:02 — 👍 1    🔁 0    💬 0    📌 0

A Comparison of Statistical Methods for Time‐To‐Event Analyses in Randomized Controlled Trials Under Non‐Proportional Hazards While well-established methods for time-to-event data are available when the proportional hazards assumption holds, there is no consensus on the best inferential approach under non-proportional hazar...

doi.org/10.1002/sim....

Our paper "A Comparison of Statistical Methods for Time-To-Event Analyses in Randomized Controlled Trials Under Non-Proportional Hazards" got published today 🎉

We describe commonly used methods, and compare their performance in a simulation study across different scenarios.

20.02.2025 14:00 — 👍 18    🔁 10    💬 2    📌 0

How should the advancement of large language models affect the practice of science? | PNAS Large language models (LLMs) are being increasingly incorporated into scientific workflows. However, we have yet to fully grasp the implications of...

An LLM "creates textual claims, and then predicts the citations that might be associated with similar text. Obviously, this practice violates all norms of scholarly citation.

At best, LLMs gesticulate toward the shoulders of giants."

Bender, West, and I contributed to this pro/con piece in PNAS.

28.01.2025 01:13 — 👍 647    🔁 157    💬 11    📌 12

Paper finally acxepted after 3 years of work on the project with a large consortium 🎉

I'll post a link, when it's published

27.01.2025 08:50 — 👍 0    🔁 0    💬 0    📌 0

Hallo, Bluesky! Folge uns für mehr! @ages.at Instagram: ages_news Facebook: AGES - Österreichische Agentur für Gesundheit und Ernährungssicherheit LinkedIn: AGES - Österreichische Agentur für Gesundheit und Ernährungssicherheit

Hallo, Bluesky! Wir sind neu hier und freuen uns, Teil dieser Community zu werden! Freut euch auf spannende Inhalte rund um die Gesundheit von Mensch, Tier, Pflanze und Umwelt. Sagt "Hi" in den Kommentaren und folgt uns für mehr! 💛 www.ages.at

10.01.2025 14:00 — 👍 19    🔁 6    💬 0    📌 1

Also imagine the work of typesetting formulae before LaTeX, ...

13.01.2025 09:43 — 👍 0    🔁 0    💬 0    📌 0

I have the greatest respect for graphics in scientific papers before computer graphics and even pen plotters were a common thing. Just beautiful 😍

13.01.2025 09:43 — 👍 0    🔁 0    💬 1    📌 0

Hi bluesky 👋

Hope there's some biostats people here, all the R people are also on mastodon but biostats wise it's been a bit lonely since leaving twitter

11.12.2024 16:22 — 👍 1    🔁 0    💬 1    📌 0

Key question to consider before submitting your paper on the development and validation of your new clinical prediction model is:

WHERE IS THE MODEL????

11.12.2024 14:30 — 👍 80    🔁 13    💬 3    📌 3