Doug Altman was an internationally renowned statistician who served as The BMJ’s chief statistical adviser.

Read about life and work that made this statistician a "citation millionaire"
#BMJChristmas
www.bmj.com/content/391/...

you forgot "_VERSION_NEW_NEW" in the title of the document! I hope you did not submit it!!

Model is: b3 <- scasm( y ~ s(x0, bs = "bs", k= k) + s(x1, bs = "sc", xt = "m+", k = k) + s(x2, bs = "bs", k = k) + s(x3, bs = "bs", k = k), family=poisson, bs=200 ) The second smooth `s(x1) is a shape constrained smooth with a positive monotonicity constraint (xt = "m+"). The `bs = 200` arguments uses 200 boostrap samples, which generates bootstrap distributions for each coefficient in the model. These bootstrap samples respect the shape constraints, while the usual +/- 2 SE credible intervals may not. The uncertainty in the partial effects is shown by two credible interval bands; a dark blue central band is a 68% Bayesian credible interval, while the lighter blue outer interval is a 95% Bayesian credible interval. The background of each panel is light grey with white grid lines, in a similar style to ggplot2's default theme.

A new release of the mgcv #RStats 📦 is out on CRAN and Simon Wood (U Edinburgh) has added some significant new features despite the small bump in version number:

🌟 scasm() for estimating GAMs with shape constrained smooths. Can be used with any family & smoothness selection is via the EFS method

They did not do an Initial data Analysis with the data they shared. They could have avoided a lot of trouble if they did. "Data sharing without regrets"... See some recommendations here: doi.org/10.1186/s128...

You do not need to see the results in order to write ~2/3 of a quant. research paper in medicine/health.

Idea for a Christmas BMJ paper: submit loads of Christmas BMJ papers, then do a survival analysis of time to rejection. Then submit the survival analysis as a Christmas BMJ paper the following year

This commentary by John B. Carlin expresses many of the concerns that I have always had with 'prognostic factor (finding) studies' and the (weird) definition of 'independent predictors': doi.org/10.1016/j.jc...

There are lots of professional data repositories to share your data (see www.re3data.org) - if you want to share the code as well you can push to github and archive it on zenodo with a DOI.

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

PS slides available at stratostg2.github.io (see activities)

Excellent collaboration with Mariana Nold, @aliaksandr-hubin.bsky.social , Michael Kammer - and #stratos TG2 - demonstrating the benefits of looking at a problem from two perspectives (n/n)

We presented 4 case studies of descriptive-predictive modeling. We generated SAPs for each study - 2 frequentist and 2 Bayesian - and included robustness checks of the resp other school. (2/n)

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)

#ISCB46 very nice talk by Michael Kammer on COVID-19 prognostic models, which involved a ‘deep dive’ into the pond life of modelling.
Bottom line: “If looking for reliable models, don’t hold your breath.”

Or a problem of confusing a descriptive task with a causal or predictive one (if you are asking me)

Variable selection is a risk factor for causal analyses. Better drop it

Rejoinder to Commentaries on: On the Uses and Abuses of Regression Models: A Call for Reform of Statistical Practice and Teaching Click on the article title to read more.

... and the rejoinder of the authors: onlinelibrary.wiley.com/doi/10.1002/... Enjoy reading! (8/8)

Discussion of “On the Uses and Abuses of Regression Models: A Call for Reform of Statistical Practice and Teaching” Click on the article title to read more.

Comment by Stijn Vansteelandt, Johan Steen: onlinelibrary.wiley.com/doi/10.1002/... (7/8)

Commentary: Regression Models—Efforts Are Required to Improve Statistical Practice and Teaching Click on the article title to read more.

Comment by the STRATOS initiative: (including @boulesteixlaure.bsky.social @mhstat.bsky.social) onlinelibrary.wiley.com/doi/10.1002/... (6/8)

Some Ways to Make Regression Modeling More Helpful Than Misleading Click on the article title to read more.

Comment by @lesdomes.bsky.social (Sander Greenland): onlinelibrary.wiley.com/doi/10.1002/... (5/8)

Commentary: Teaching Statistics as Minor Subject—Handing on Fire, Not Worshipping Ashes Click on the article title to read more.

Comment by Mariana Nold and myself: onlinelibrary.wiley.com/doi/10.1002/... (4/8)

To Explain, to Predict, or to Describe: Figuring out the Study Goal [Commentary on “On the Uses and Abuses of Regression Models” by Carlin and Moreno‐Betancur] I strongly support Carlin and Moreno-Betancur's assertion that regression modeling (and in fact, any modeling) should be driven by the type of research question: descriptive, predictive, or causal. I...

Comment by Galit Shmueli: onlinelibrary.wiley.com/doi/10.1002/... (3/8)

Regression—A Means, Not an End Click on the article title to read more.

Along with several comments: the first one by Robert Platt appeared already in an earlier issue: onlinelibrary.wiley.com/doi/10.1002/... (2/8)

Published: the paper 'On the uses and abuses of Regression Models: a Call for Reform of Statistical Practice and Teaching' by John Carlin and Margarita Moreno-Betancur in the latest issue of Statistics in Medicine onlinelibrary.wiley.com/doi/10.1002/... (1/8)

Summary Song #9 - Overfitting (Stats Parody - Charlie Puth Attention) YouTube video by The Raf

This is taking statistical education to the next level: www.youtube.com/watch?v=pZTL... by Rafael de Andrade Moral, Maynooth University

Regression with Highly Correlated Predictors: Variable Omission Is Not the Solution - PubMed Regression models have been in use for decades to explore and quantify the association between a dependent response and several independent variables in environmental sciences, epidemiology and public...

pubmed.ncbi.nlm.nih.gov/33920501/

Flexible parametrization of graph‐theoretical features from individual‐specific networks for prediction Statistical techniques are needed to analyze data structures with complex dependencies such that clinically useful information can be extracted. Individual-specific networks, which capture dependenci....

I am proud to have authored this with Sean, who provided his invaluable and unique expertise at the intersection of statistics and networks: doi.org/10.1002/sim....

Continuing our #BlackHistoryMonth series, we celebrate Sean Simpson, Professor of Biostatistics & Data Science, for his contributions to neuroimaging analysis, repeated measures, & covariance modeling. Outside of work, he enjoys time with his wife, statistician Felicia, and their daughter Sophia.

Happy and proud to be on this impressive author list: @maartenvsmeden.bsky.social @laurewynants.bsky.social @benvancalster.bsky.social @richarddriley.bsky.social @pauladhiman.bsky.social @gscollins.bsky.social @kdpsingh.bsky.social and many more, masterfully led by Karel Moons!

PROBAST+AI: an updated quality, risk of bias, and applicability assessment tool for prediction models using regression or artificial intelligence methods The Prediction model Risk Of Bias ASsessment Tool (PROBAST) is used to assess the quality, risk of bias, and applicability of prediction models or algorithms and of prediction model/algorithm studies....

www.bmj.com/content/388/...