In battenr/rwetasks: Tasks Associated with RWE Projects

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

rwetasks

rwetasks has simple functions for performing common tasks, such as calculating the number (and proportion) of people: in each age group, receiving a specific treatment, annualizing healthcare costs and how different inclusion criteria affects the sample size. It was built for anyone working with real-world data (RWDD) in mind, however experienced R users can already do everything covered here. rwetasks is aimed at improving speed of simple tasks, so you can use your brain power for the more complex stuff!

Status: Currently in development, not officially released yet (aka not ready for prime time)

Installation

The development version from GitHub with:

# install.packages("devtools")
devtools::install_github("battenr/rwetasks")

Using rwetasks

mean_by_group

mean_by_group provides a way to calculate the mean for each group. Can also be used across a dataframe when you want to calculate mean(sd) for each group for every variable

library(tidyverse)
library(rwetasks)

rwetasks::mean_by_group(mtcars, mpg, gear)

# Can also use across a dataframe like so

mtcars %>%
  purrr::map(
    ~mean_by_group(mtcars, .x, gear)
  )

count_percent

count_percent provides a way to quickly calculate the number (n) and proportion of each value of a variable, arranged by proportion.

library(tidyverse)
library(rwetasks)

rwetasks::count_percent(mtcars, gear)

count_percent_demo

count_percent_demo provides a way to quickly calculate the number (n) and proportion of each value of a variable, when you have multiple measures per participants (i.e., if you have longitudinal data, but want to calculate proportion of females for participants).

library(tidyverse)
library(rwetasks)

rwetasks::count_percent_demo(iris, Species, Petal.Width)

battenr/rwetasks documentation built on Jan. 21, 2022, 12:22 a.m.