PumasAI/Bayesian-Workshop

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Created about 2 years ago
Updated about 1 year ago

PumasAI/Bayesian-Workshop

PumasAI

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Slides for Bayesian Workshops across the world

SimpleChains.jl

QuartoNotebookRunner.jl

SummaryTables.jl

A Julia package for creating publication-ready summary tables in HTML, docx, LaTeX and Typst

WriteDocx.jl

A Julia package to create docx files for Microsoft Word from scratch

sensitivity_analysis_paper

WCoP2022_Pumas_Workshop

add-private-registry

This GitHub Action adds a private Julia package registry from a Pkg Server

nm_highlighter

ACoP13_NLME_Workshop

Pumas NLME workshop material for ACoP 13

Pumas_Workshop_Tokyo_2022

Pumas workshop for our friends in Japan.

PackageBundler.jl

Experimental bundling of Julia packages and environments.

Optimal-Design-Workshop

Workshop for Optimal Design in Pumas - Slides and Code

Git-Tutorial

Temporary Git Repository for a Git/GiHub Workshop

MBDD-MCC-135

The sample size calculation using modeling & simulation approach is considered to be more efficient than conventional modeling. The proposal is to compare the power of defining the exposure-response, and thereby establishing efficacy, using model-based approaches. Specifically, a base exposure-IGA score (ordinal scale) relationship will be assumed. Data will be simulated and subjected to conventional and model-based analyses. The model-based approach can test single-point (end of the study) and longitudinal models. The power of the two approaches will be compared. The process will be repeated for different ‘what-if’ scenarios from the base model. Several details of the simulations are provided by MTPC during the exploratory meeting.