Just discovered the Causal Quartet by @lucystats.bsky.social@travisgerke.bsky.social@malcolmbarrett.malco.io#rstats

Therein lies the problem- we will likely not know what their baseline is. Same goes with BP and using this for vasopressor titration (instead we use a universal MAP). How do we get around this?

Here is a blog post on using Generalized Additive Models (GAMs) for meta-analysis or, more specifically, meta-regression in {brms}: matthewbjane.com/blog-posts/b...

Generalized Additive Models (GAMs) for Meta-Regression using brms – Matthew B. Jané

A GAM is a linear or generalized linear model that allows you to model non-linear relationships using splines, smooth functions that allows to model the “wiggiliness” in the data. To my knowledge ther...

Screams in diabetic...

As suggested by Tim, let’s look back at one of my early papers as a skeetutorial. I haven’t looked at this paper probably since it was published, so let’s see if I learned anything in the past 8 years #EpiSkybsky.app/profile/timp...

@hadleywickham.bsky.social@posit.co

Have just written my favorite response to a reviewer comment ever

With #TargetTrialedhub.ama-assn.org/jn-learning/...

Target Trial Emulation for Causal Inference From Observational Data With Dr Hernán

Miguel A. Hernán, MD, DrPH, professor of epidemiology, Harvard T.H. Chan School of Public Health, discusses Target Trial Emulation: A Framework for Causal Inference From Observational Data with JAMA Statistical Editor Roger J. Lewis, MD, PhD.

"Ratios in regression analyses with causal questions" - interesting new paper in @amjepi.bsky.social#EpiSkyacademic.oup.com/aje/advance-...