Tobias Fellinger

@stats-tobby.bsky.social

Interested in biostats, R, regulatory science, clinical trials, time to event analysis, causal inference, ... he/him

one of my favourite experiences in writing art code is when the code base is just complex enough that you can almost predict what it will produce, but not quite, leading to pieces that aren't exactly what you were expecting #rstats

abstract artwork in a blue/orange/off-white palette. comprised of several irregularly spaced vertical bands with rough edges, with streaks and protrusions running through the image

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/...

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

academic.oup.com

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.

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

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.

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...

pnas.org