Gordon Forbes
@gforb.bsky.social
I love Netflix for their data science blog and The BBC for their ggplot2 resources.
Did you spend 4-6 weeks writing your last analysis plan then get mocked by statisticians on the internet for being slow 😜. We had a go doing it with AI - still takes 4-6 weeks but the AI will do the boring parts letting you conentrate on the stats. Pre print-here bsky.app/profile/gfor...
Darren Dahly@statsepi.bsky.social · 6mo agoI'd be curious to know why it takes 4-6 weeks to develop a SAP if you have the protocol and an existing wealth of experience developing SAPs from protocols.
We’ve just released a pre-print reporting the development and validation of an AI tool to write statistical analysis plans from protocols. www.linkedin.com/feed/update/... Thread 👇
From Protocol to Analysis Plan: Development and Validation of a Large Language Model Pipeline for Statistical Analysis Plan Generation using Artificial Intelligence (SAPAI) | Petrina C.
Are you a trial statistician who’s tired of manually transferring details from a protocol to a blank analysis plan template? Have you ever wished AI could draft that first version for you? Introdu...
linkedin.com
fucking FINALLY
Daniel E. Weeks@statgendan.bsky.social · 6mo agoThe canvas() function from the ggview R package is very useful for previewing/tweaking a ggplot into publication-ready format: it renders a plot "as it would appear if saved to a file with the specified dimensions". cran.r-project.org/web/packages... #RStats #ggplot #ggview
We've got something cooking along thse lines. Anyone else?
Matt Parkes@mattyjparkes.bsky.social · 6mo agoHaving complicated feelings about this one…
Hey #rstats, What's your rule for splitting R scripts that form part of a wider analysis pipeline / project? I usually write a single script which includes sections for each step from data cleaning to the final results, but it can become unwieldy when the script becomes long. ...
New paper posted on Arxiv: "When do composite estimands answer non-causal questions?" This can happen more often than you think, and can have a dramatic impact on trial results (e.g. a false-positive rate of almost 90%) arxiv.org/abs/2506.22610 @timpmorris.bsky.social
When do composite estimands answer non-causal questions?
Under a composite estimand strategy, the occurrence of the intercurrent event is incorporated into the endpoint definition, for instance by assigning a poor outcome value to patients who experience th...
arxiv.org
On tabular health data, time and time again, I see linear (or generalised linear models) perform as well or better than machine learning algorithms that avoid linearity assumptions. I am surprised by this, as the linearity assumption is unlikely to be true. Does anyone else see this? Why is this?
Georgi Baklicharov asks: can treatment effect testing in trials with intercurrent events be nearly assumption-free? #EuroCIM2025
Happy to see that ordered beta regression reached 100 citations on Google Scholar! The model has citations from work in climate science, ecology, medicine, psychology, & political science, just to name a few. Thanks to all of you for using ordbetareg (or glmmTMB)!! #rstats
I'm working with data that I'm not allowed to share -- I'd like to generate synthetic data so that others at least have something that they can run my code on! Any pointers to tutorials, favorite packages etc.?
a man wearing a mask is playing a keyboard with the words love synths written above him
ALT: a man wearing a mask is playing a keyboard with the words love synths written above him
media.tenor.com
Check out my new screencast, where I walk through how I use #Positron for #rstats package development work. I decided to release a new version of an R package to CRAN ✨live✨ this time around! youtu.be/uL3NZQIMrpk
Release an R package with Positron
YouTube video by Julia Silge
youtu.be
In coursework, the contrast between ridge regression and the LASSO is really emphasized. After all, the latter actually does feature selection, by virtue of having a sparse solution to the minimum l1 problem, versus ridge's nonsparse solution in l2, pretty cool. 1/2
We tried to look at ways to obtain flexible calibration plots in clustered (e.g. multicenter) validation studies. Work with @lasaibarrenada.bsky.social @laurewynants.bsky.social @bavodccampo.bsky.social arxiv.org/abs/2503.08389
Clustered Flexible Calibration Plots For Binary Outcomes Using Random Effects Modeling
Evaluation of clinical prediction models across multiple clusters, whether centers or datasets, is becoming increasingly common. A comprehensive evaluation includes an assessment of the agreement betw...
arxiv.org
The term "digital twin" as it is now used in medicine has no real relationship to how the term is used in engineering. Yet every paper on the former talks about the success of the latter as if that's relevant. They are not the same!
My spell check is trying to change bootstrap to Boomer. As in Boomer p-values. I didn't know the generation wars had made it to statistical inference. What next? Millennial credible intervals?
It's amazing how far back ideas go. This paper from 1984 by @f2harrell.bsky.social discusses the need for train/test data splits and the importance of assessing model calibration and discrimination and instability in variable selection methods. onlinelibrary.wiley.com/doi/epdf/10....
Regression modelling strategies for improved prognostic prediction
Regression models such as the Cox proportional hazards model have had increasing use in modelling and estimating the prognosis of patients with a variety of diseases. Many applications involve a larg...
onlinelibrary.wiley.com
A minor stylistic preference I’ve recently found myself using: When introducing a key initialism or acronym in a paper, put the compressed version in the text and its expansion in parentheses. Instead of ‘under missing at random (MAR)’, use ‘under MAR (missing at random)’. 1/
What advice do folks have for organising projects that will be deployed to production? How do you organise your directories? What do you do if you're deploying multiple "things" (e.g. an app and an api) from the same project?
Just published a couple of pre-prints for those interested in sample size calculations for precise and fair individual-level predictions ... (not the end of the story, but a useful contribution we hope): Binary outcomes: arxiv.org/abs/2407.09293 Survival outcomes: arxiv.org/abs/2501.14482
A decomposition of Fisher's information to inform sample size for developing fair and precise clinical prediction models -- part 1: binary outcomes
When developing a clinical prediction model, the sample size of the development dataset is a key consideration. Small sample sizes lead to greater concerns of overfitting, instability, poor performanc...
arxiv.org
Am looking for a particular article that argued that results of "explanatory" trials might generally be more timeless than those of pragmatic trials, since the latter might be reliant on a particular context at a given moment in time. Can't remember who this was by - something from imp science lit?
'Estimating hypothetical estimands with causal inference and missing data estimators in a diabetes trial case study', led by Camila Olarte Parra, with Rhian Daniel and David Wright, now available open access in Biometrics: doi.org/10.1093/biom...
Estimating hypothetical estimands with causal inference and missing data estimators in a diabetes trial case study
ABSTRACT. The ICH E9 addendum on estimands in clinical trials provides a framework for precisely defining the treatment effect that is to be estimated, but
doi.org
#statstab #267 That’s a Lot to Process! Pitfalls of Popular Path Models Thoughts: The number of senior psych researchers that just loooove Process...and all use it post hoc 😩 Causal inference is not easy. #mediation #process #spss #causalinference #SEM journals.sagepub.com/doi/10.1177/...
That’s a Lot to Process! Pitfalls of Popular Path Models - Julia M. Rohrer, Paul Hünermund, Ruben C. Arslan, Malte Elson, 2022
Path models to test claims about mediation and moderation are a staple of psychology. But applied researchers may sometimes not understand the underlying causal...
journals.sagepub.com
"Many widely used models amount to an elaborate means of making up numbers—but once a number has been produced, it tends to be taken seriously and its source (the model) is rarely examined carefully." Ouch. doi.org/10.1007/s000...
Pay No Attention to the Model Behind the Curtain - Pure and Applied Geophysics
Many widely used models amount to an elaborate means of making up numbers—but once a number has been produced, it tends to be taken seriously and its source (the model) is rarely examined carefully. M...
doi.org
What is the best way to create a blog for #rstats content? Is it quarto blogs or are there better ways to do it?
