SurgicalInformatics / healthyr_notebooks_materialsLinks
Scroll down this page for installation instructions, or see this poster:
☆24Updated 4 months ago
Alternatives and similar repositories for healthyr_notebooks_materials
Users that are interested in healthyr_notebooks_materials are comparing it to the libraries listed below
Sorting:
- Good Software Engineering Practice for R Packages @ Rockville, MD☆11Updated last year
- Wrangling survival data☆21Updated 6 years ago
- ☆13Updated 4 months ago
- ☆10Updated 3 years ago
- A simple template for fitting tidymodels in R☆11Updated 11 months ago
- Data Package for Medical Datasets☆59Updated 2 years ago
- Collection of links and source code for stat education resources made in Shiny☆62Updated 5 years ago
- Source and slides for "Why you should be using tidymodels" at UW-Madison☆18Updated last year
- Health economic simulation modeling and decision analysis☆73Updated 2 months ago
- ☆18Updated 3 years ago
- Introduction to ML with R using tidymodels☆49Updated 3 years ago
- Workshop - Clinical Tables in R with gt☆19Updated 2 years ago
- Example content for Reporting and Presentation webinar☆29Updated 2 years ago
- Slides for my R/Medicine 2022 talk, "Making Swimmer Plots for Longitudinal Data using {ggplot}".☆11Updated 3 years ago
- e-Rum2020::A Unified Approach For Writing Automatic Reports☆20Updated 5 years ago
- One day Shiny training for health and care analysts☆39Updated 3 years ago
- The repository contains case studies contributed from companies and individuals, who are implementing a risk-based approach to validate R…☆24Updated 2 years ago
- Analysis of simulation studies including Monte Carlo error☆30Updated last year
- Techniques to Build Better Balance in Propensity Score Models☆20Updated last month
- R package for microsimulation☆41Updated 3 months ago
- The material for the R/Pharma workshop about end to end clinical trials☆27Updated 2 years ago
- High dimensional propensity score algorithm in R☆30Updated 8 years ago
- DataFakeR is an R package designed to help you generate sample of fake data preserving specified assumptions about the original one.☆33Updated 2 years ago
- ☆11Updated last year
- Data Cleaning workshop for the 2023 R/Medicine Conference☆16Updated last year
- ☆26Updated 2 years ago
- ☆42Updated 3 years ago
- Principles & Practice of Data Visualization, CS631 Spring 2018☆38Updated 6 years ago
- ☆44Updated 3 years ago
- https://mastering-shiny-solutions.org☆19Updated 2 years ago