Can anyone recommend tools for collaborating on latex files?? Looking for something friendly to ppl with little tech background (no git) and with capacity for adding comments.
There's overleaf but it's expensive and limits the number of collaborators
Great stuff! Are you finding that julia works well with nix? There were issues I remember related to some julia libraries (e.g Plots) on NixOS.
I can imagine that using T with a pipeline based on julia and R nodes would be super useful
In fact not just IMO*
pubmed.ncbi.nlm.nih.gov/29966732/
The PP effect is the most relevant estimand for those patients who do expect to adhere, IMO. Plus, the ITT effect in the trial population (with unusually high adherence) will differ from the ITT effect in routine practice, or in other pops with different adherence patterns, unlike the PP effect
Certainly for *naive* per protocol analyses, but well conducted per protocol analyses are still useful. Can overcome some issues with ITT effects (e.g. relevance, adherence dependence, generalisability). Identification does require assumptions, but same goes for ITT effects in realistic trials!
It's also great having all your important configs managed declaratively in one place and committed to git. Any changes you make are easy to track and undo. Plus, because your whole set up is managed by a config file(s), you can reproduce it exactly across any number of machines
Big appeal is that it solves all the issues you describe above! Because the whole system is managed declaratively, if everything gets borked, just wind back to a previous build. And if you want latest software, easy, set nixpkgs to unstable. Or use unstable for neovim and leave others at stable
Time for NixOS??
You would rather someone share code without a targets pipeline rather than with one?? Why?
I don't use rix but use nix directly for project environments. I've got to say it's incredibly convenient, even besides the reproducibility benefit. The ability to drop into any project with any set of dependencies and it just works, no matter how old. Incredible. Worth some initial pain imo!
Really? I can think of some common use cases. For example, if you want to use biomarkers to predict disease but are constrained in what you can measure in practice, you may want to know which subset of biomarkers is the most "important" (e.g. in terms of R^2, PPV, etc)
Also tar_map_rep for simulation studies/bootstrapping. The parallelization with crew is so fast and clean. Will Landau is making such good software
Other end of the spectrum: www.nytimes.com/2025/12/16/o...
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Courses include causal inference, cluster randomised trials, meta-analysis and the estimand framework.
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#statistics
Science people!!
What software are you using to draft papers (besides MS Word 🤮)? Looking for something that
1. Allows for easy collab (with non-tech ppl, so latex is out)
2. In format accepted by journals (so no typst?)
3. Has reference manager integration
Is it just googledocs/libreoffice?
Just to note, shared folders on google drive etc (anything that syncs changes) can be a real nightmare if you do end up collaborating via git & github
Frequentist alternative to Bayesian model averaging: Incorporate all 6 specifications into a superlearner stack, letting the data dictate how much weight each model receives in the ensemble. (Might need a doubly robust estimator/bootstrapping for valid inference). cran.r-project.org/web/packages...
That's great! With MSM's, is it straightforward to incorporate the estimation of the weights and the weighting of the regression model (Y on A*) with those estimated weights?
