Project workflow skills for health economics modelling in R

intro image here — Data science workflow

Where: The New Bath Hotel, Matlock
Participants: ScHARR, University of Sheffield (see program for details of lecture rooms)
Date: 3^rd August 2022
Time: 09:00-17:30
Instructor: Nathan Green

Learn about the data science of health economics modelling workflow in R.

Prerequisites

Basic R and maths

Learning Objectives

From basic principles to advanced coding. You will be able to

Write `clean code’
Understand package workflows in RStudio
Write Functions
Use tidyverse
Do basic debugging
Unit testing
Document your code

Software

Required software:

R (free general statistical software)
RStudio

We suggest all participants bring a laptop on which they have installed these already.

Installation

The following sets out a basic installation process:

If necessary download and install R and potentially a user interface to R like RStudio.

Once R and Rstudio are both installed, if you open RStudio and things have gone according to plan then in the console you will see something like the following:

R version 3.6.1 (2019-07-05) -- "Action of the Toes"
Copyright (C) 2019 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64 (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

Install Necessary Packages

Open RStudio and paste the following code into your console, then press Enter to run it:

# Download packages from CRAN

install.packages(c("devtools", "knitr", "magrittr", "rmarkdown", "usethis", "ggplot2", "dplyr", "reshape2", "purrr", "lintr"))

These are the main packages for the workshop. If we require more then we can either install them from the web or from e.g. a USB if we have them.

The workshop webpage is here
The associated GitHub Repository is here

We suggest downloading the repo content to your computer, either via git clone or the .zip folder if you prefer.

Target audience

The course is open to everyone with an interest in health economics modelling and R.