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accrualPlot

An R package for creating accrual plots

https://github.com/ctu-bern/accrualplot

Science Score: 13.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ○
    .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ○
    Committers with academic emails
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (19.6%) to scientific vocabulary

Keywords

recruitment

Keywords from Contributors

confidence-intervals precision sample-size-calculation shiny-app
Last synced: 11 months ago · JSON representation

Repository

An R package for creating accrual plots

Basic Info
Statistics
  • Stars: 3
  • Watchers: 1
  • Forks: 3
  • Open Issues: 5
  • Releases: 0
Topics
recruitment
Created over 5 years ago · Last pushed almost 2 years ago
Metadata Files
Readme Changelog License

README.Rmd 

---
output: github_document
---



```{r, echo = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-"
)
```

# `accrualPlot` 


[![](https://www.r-pkg.org/badges/version/accrualPlot?color=green)](https://cran.r-project.org/package=accrualPlot)
`r badger::badge_custom("dev version", as.character(packageVersion("accrualPlot")), "blue", "https://github.com/CTU-Bern/accrualPlot")`
[![Actions Status](https://github.com/CTU-Bern/accrualPlot/workflows/R-CMD-check/badge.svg)](https://github.com/CTU-Bern/accrualPlot/actions)
[![metacran downloads](https://cranlogs.r-pkg.org/badges/grand-total/accrualPlot)](https://cran.r-project.org/package=accrualPlot)




Accrual plots are an important tool when monitoring clinical trials. Some trials are terminated early due to low accrual, which is a waste of resources (including time). Assessing accrual rates can also be useful for planning analyses and estimating how long a trial needs to continue recruiting participants.  `accrualPlot` provides tools for such plots

## Installation

`accrualPlot` can be installed from CRAN in the usual manner:

```{r cran-installation, eval = FALSE}
install.packages('accrualPlot')
```

The development version of the package can be installed from the CTU Bern universe via

```{r universe-installation, eval = FALSE}
install.packages('accrualPlot', repos = c('https://ctu-bern.r-universe.dev', 'https://cloud.r-project.org'))
```

`accrualPlot` can be installed directly from from github with:

```{r gh-installation, eval = FALSE}
# install.packages("remotes")
remotes::install_github("CTU-Bern/accrualPlot")
```

Note that `remotes` treats any warnings (e.g. that a certain package was built under a different version of R) as errors. If you see such an error, run the following line and try again:

```{r remotes-error, eval = FALSE}
Sys.setenv(R_REMOTES_NO_ERRORS_FROM_WARNINGS = "true")
```

## Overview
The first step to using `accrualPlot` is to create an accrual dataframe. This is simply a dataframe with a counts of participants included per day.

```{r}
# load package
library(accrualPlot)

# demonstration data
data(accrualdemo)

df <- accrual_create_df(accrualdemo$date)

```

Cumulative and absolute recruitment plots , as well as a method to predict the time point of study completion, are included.

```{r, fig.height=3, fig.width=7.5}
par(mfrow = c(1,3))
plot(df, which = "cum")
plot(df, which = "abs")
plot(df, which = "pred", target = 300)
```

### Acknowledgements

The package logo was created with [`ggplot2`](https://ggplot2.tidyverse.org/) and [`hexSticker`](https://github.com/GuangchuangYu/hexSticker) with icons from [Font Awesome](https://fontawesome.com/) (via the [emojifont package](https://github.com/GuangchuangYu/emojifont)).

Owner

  • Name: CTU Bern
  • Login: CTU-Bern
  • Kind: organization
  • Location: Switzerland

CTU Bern is the Clinical Trials Unit of the Faculty of Medicine of the University of Bern and the Inselspital, Bern University Hospital.

GitHub Events

Total
Last Year

Committers

Last synced: over 3 years ago

All Time
  • Total Commits: 296
  • Total Committers: 9
  • Avg Commits per committer: 32.889
  • Development Distribution Score (DDS): 0.595
Top Committers
Name Email Commits
aghaynes a****s@g****m 120
lbueti l****r@c****h 52
Alan Haynes a****s@u****m 49
GitHub Actions a****s@g****m 45
Render action r****n@g****m 22
Lukas Bütikofer 5****i@u****m 5
runner r****r@M****l 1
Haynes h****s@c****h 1
runner r****r@M****l 1
Committer Domains (Top 20 + Academic)
github.com: 2 campus.unibe.ch: 1 ctu.unibe.ch: 1

Issues and Pull Requests

Last synced: 12 months ago

All Time
  • Total issues: 10
  • Total pull requests: 49
  • Average time to close issues: about 2 months
  • Average time to close pull requests: 8 days
  • Total issue authors: 3
  • Total pull request authors: 2
  • Average comments per issue: 0.6
  • Average comments per pull request: 0.22
  • Merged pull requests: 49
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 1
  • Average time to close issues: N/A
  • Average time to close pull requests: 3 minutes
  • Issue authors: 0
  • Pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 0.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • aghaynes (8)
  • Robinmoon26 (1)
  • ArnaudKunzi (1)
Pull Request Authors
  • lbueti (26)
  • aghaynes (23)
Top Labels
Issue Labels
enhancement (3) documentation (1)
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • cran 334 last-month
  • Total docker downloads: 21,613
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 2
  • Total maintainers: 1
cran.r-project.org: accrualPlot

Accrual Plots and Predictions for Clinical Trials

  • Versions: 2
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 334 Last month
  • Docker Downloads: 21,613
Rankings
Forks count: 17.8%
Stargazers count: 28.5%
Average: 29.0%
Dependent packages count: 29.8%
Downloads: 33.6%
Dependent repos count: 35.5%
Maintainers (1)
lukas.buetikofer@ctu.unibe.ch
Last synced: 12 months ago

Dependencies

DESCRIPTION cran
  • R >= 2.10 depends
  • lubridate * depends
  • dplyr * imports
  • ggplot2 * imports
  • grid * imports
  • magrittr * imports
  • purrr * imports
  • rlang * imports
  • knitr * suggests
  • markdown * suggests
  • patchwork * suggests
  • rmarkdown * suggests
  • testthat * suggests
  • vdiffr * suggests