Georg Heinze

@georgheinze.bsky.social

Biostatistician, prognosis researcher, beginner.

Given that now some reviewers let AI do the job, how can we convince an AI reviewer that was prompted as „your role: grumpy reviewer 2“? (And who prevents them from uploading our ideas, for free, to OpenAI&co?)

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

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.

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

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.

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I was just wondering what would have happened if the development had been the other way around. If machine learning had existed beforehand and regression analysis had only been invented afterwards.

We have two vacancies for a postdoctoral and PhD researcher at Maastricht University. They will work on the development and application of value-of-information methods for the validation of clinical risk prediction models and medical AI. links below

PhD in Epidemiology on value-of-information from validating clinical prediction models and AI

PhD in Epidemiology on value-of-information from validating clinical prediction models and AI

vacancies.maastrichtuniversity.nl

Statistical Thinking Across Borders: Building Bridges and Expanding Horizons in Clinical Biostatistics at the 46th Annual Conference of the ISCB (International Society for Clinical Biostatistics), this time in the Trinational Eurodistrict of Basel, Switzerland, from August 24th to 28th, 2025.