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SNEAK PREVIEW: Complete Path Enumeration (CPE) for CRM #dosefinding designs
Featuring a vignette for #Rstats package #precautionary update v0.2-3, currently under review by CRAN. 1/
precisionmethods.guru/DTAT/CPE/MCSE-…
Featuring a vignette for #Rstats package #precautionary update v0.2-3, currently under review by CRAN. 1/
precisionmethods.guru/DTAT/CPE/MCSE-…
This demonstrates the feasibility of a programme I’ve set forth, for the ‘exact’ simulation of ANY dose-escalation design.
Influenced by @MarkusTriska‘s exacting perspective on ’exactness’, however, I now use the more precise term ‘MCSE-free’. 2/
Influenced by @MarkusTriska‘s exacting perspective on ’exactness’, however, I now use the more precise term ‘MCSE-free’. 2/
@MarkusTriska ‘MCSE-free’ in turn alludes to the title of recent work by Thomas M. Braun, from which I adapt my application.
(Braun’s mean-field approach truly can be called ‘simulation-free’, whereas I DO simulate the trials—just without Monte Carlo error.) 3/
(Braun’s mean-field approach truly can be called ‘simulation-free’, whereas I DO simulate the trials—just without Monte Carlo error.) 3/
My first piece on #multiomics #IBD as part of my thesis is out as a preprint!
I'll summarize it on this thread
medrxiv.org/content/10.110…
I'll summarize it on this thread
medrxiv.org/content/10.110…
First, we check how the many parameters of RGCCA #rstats influence and work in their original dataset. We check that different designs select different variables, we discard the superblock design.
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Then we look our own dataset of #IBD samples undergoing a treatment and some controls. We use a method to find good models of the data. The method is available as #rstats package, with its own #pkgdown website llrs.github.io/inteRmodel/
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