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README.Rmd
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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r setup, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "90%",
fig.width= 12,
fig.height=3)
fig_count <- 1
```
# robvis <img src="man/figures/robvis_hex_box.png" align="right" width="18%" height="18%" />
[![Project Status: Active – The project has reached a stable, usable state and is being actively developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)
[![CRAN Badge.](https://www.r-pkg.org/badges/version-ago/robvis)](https://CRAN.R-project.org/package=robvis)
[![CRAN Downloads.](https://cranlogs.r-pkg.org/badges/last-month/robvis)](https://CRAN.R-project.org/package=robvis)
<br>
[![R build status](https://github.com/mcguinlu/robvis/workflows/R-CMD-check/badge.svg)](https://github.com/mcguinlu/robvis/actions)
[![Codecov test coverage](https://codecov.io/gh/mcguinlu/robvis/branch/master/graph/badge.svg)](https://codecov.io/gh/mcguinlu/robvis?branch=master)
<br>
[![DOI](https://img.shields.io/static/v1.svg?label=Publication&message=10.1002/jrsm.1411&color=informational)](https://doi.org/10.1002/jrsm.1411)
[![metaverse Identifier](https://img.shields.io/static/v1.svg?label=Part%20of%20the&message=metaverse&color=informational)](https://www.github.com/rmetaverse/metaverse)
**UPDATE**: `robvis` now exists as a [web-app](https://mcguinlu.shinyapps.io/robvis), aimed at those who are not familiar with R or who want to explore the package's functionality before installing it locally.
## Description
```{r include = FALSE}
library(robvis)
library(kableExtra)
library(magrittr)
```
The `robvis` package takes the summary table from risk-of-bias assessments and produces plots formatted according to the assessment tool used.
## Getting started
Install the development version which contains new functionality and a range of bug fixes:
```{r, eval=FALSE}
install.packages("devtools")
devtools::install_github("mcguinlu/robvis")
```
To update the package, run the `install_github("mcguinlu/robvis")` command again.
If you wish to use the older CRAN version of the package, use the following command:
```{r, eval=FALSE}
install.packages("robvis")
```
### Load data
To load your own data from a .csv file:
```{r, eval=FALSE}
mydata <- read.csv("path/to/mydata.csv", header = TRUE)
```
To help users explore `robvis`, we have included example datasets in the package, one for each of the tool templates that currently exist within the package. The `data_rob2` dataset ([view it here](https://github.com/mcguinlu/robvis/blob/master/data_raw/data_rob2.csv)), which contains example risk-of-bias assessments performed using the RoB2.0 tool for randomized controlled trials, is used to create the plots in subsequent sections.
### Create plots
The package contains two plotting functions:
#### 1. rob_summary()
Returns a ggplot object displaying a bar-chart of the risk of bias of included studies across the domains of the specified tool. [*Note: the defaults used in this function have changed from their original settings, so that a un-weighted barplot is now produced by default. See the NEWS.md file for further information.*]
```{r, eval = FALSE}
summary_rob <- rob_summary(data = data_rob2, tool = "ROB2")
summary_rob
```
``` {r, echo = FALSE}
plot <- rob_summary(data = data_rob2, tool = "ROB2")
file = paste0("man/figures/robplot",fig_count,".png")
rob_save(plot, file)
fig_count <- fig_count + 1
```
<div style="text-align:center"><img src=`r file` width="70%" height="70%"/></div>
#### 2. rob_traffic_light()
Returns a ggplot object displaying a ["traffic light plot"](https://handbook-5-1.cochrane.org/chapter_8/figure_8_6_c_example_of_a_risk_of_bias_summary_figure.htm), displaying the risk of bias judgment in each domain for each study.
```{r, eval=FALSE}
trafficlight_rob <- rob_traffic_light(data = data_rob2,
tool = "ROB2",
psize = 10)
trafficlight_rob
```
``` {r, echo = FALSE}
plot <- rob_traffic_light(data = data_rob2,
tool = "ROB2",
psize = 10)
file = paste0("man/figures/robplot",fig_count,".png")
rob_save(plot, file)
fig_count <- fig_count + 1
```
<div style="text-align:center"><img src=`r file` width="70%" height="70%"/></div>
### Other functions
#### rob_save()
Pass the `robvis` to this function, along with a destination file, to save your risk-of-bias plots using sensible defaults.
```{r, eval = FALSE}
rob_save(trafficlight_rob, "rob_fig.png")
```
#### rob_tools()
Outputs a list of the risk of bias assessment tools for which a template currently exists in rob_summary(). We expect this list to be updated in the near future to include tools such as ROBIS (tool for assessing risk of bias in systematic reviews).
```{r}
rob_tools()
```
## Advanced usage
### Change the colour scheme
The `colour` argument of both plotting functions allows users to select from two predefined colour schemes ("cochrane" or "colourblind") or to define their own palette by providing a vector of hex codes.
For example, to use the predefined "colourblind" palette:
```{r, eval=FALSE}
rob_summary(data = data_rob2,
tool = "ROB2",
colour = "colourblind")
```
``` {r, echo = FALSE}
plot <- rob_summary(data = data_rob2,
tool = "ROB2",
colour = "colourblind")
file = paste0("man/figures/robplot",fig_count,".png")
rob_save(plot, file)
fig_count <- fig_count + 1
```
<div style="text-align:center"><img src=`r file` width="70%" height="70%"/></div>
And to define your own colour scheme:
```{r, eval=FALSE}
rob_summary(
data = data_rob2,
tool = "ROB2",
colour = c("#f442c8",
"#bef441",
"#000000",
"#d16684")
)
```
``` {r, echo = FALSE}
plot <- rob_summary(data = data_rob2,
tool = "ROB2",
colour = c("#f442c8",
"#bef441",
"#000000",
"#d16684"))
file = paste0("man/figures/robplot",fig_count,".png")
rob_save(plot, file)
fig_count <- fig_count + 1
```
<div style="text-align:center"><img src=`r file` width="70%" height="70%"/></div>
### No "Overall" judgement
By default, both functions include an "Overall" risk of bias domain. To prevent this, set `overall = FALSE`.
```{r, eval=FALSE}
summary_rob <- rob_summary(data = data_rob2, tool = "ROB2", overall = FALSE)
summary_rob
```
``` {r, echo = FALSE}
plot <- rob_summary(data = data_rob2, tool = "ROB2", overall = FALSE)
file = paste0("man/figures/robplot",fig_count,".png")
rob_save(plot, file)
fig_count <- fig_count + 1
```
<div style="text-align:center"><img src=`r file` width="70%" height="70%"/></div>
```{r, eval=FALSE}
rob_traffic_light(data = data_rob2,
tool = "ROB2",
overall = FALSE)
```
``` {r, echo = FALSE}
plot <- rob_traffic_light(data = data_rob2,
tool = "ROB2",
overall = FALSE)
file = paste0("man/figures/robplot",fig_count,".png")
rob_save(plot, file)
fig_count <- fig_count + 1
```
<div style="text-align:center"><img src=`r file` width="70%" height="70%"/></div>
### Editing the plots
Finally, because the output (`summary_rob` and `trafficlight_rob` in the examples above) is a ggplot2 object, it is easy to adjust the plot to your own preferences.
For example, to add a title:
```{r, eval=FALSE}
library(ggplot2)
rob_summary(data = data_rob2, tool = "ROB2") +
ggtitle("Summary of RoB 2.0 assessments")
```
``` {r, echo = FALSE}
plot <- rob_summary(data = data_rob2, tool = "ROB2") +
ggplot2::ggtitle("Summary of RoB2.0 assessments")
file = paste0("man/figures/robplot",fig_count,".png")
rob_save(plot, file)
fig_count <- fig_count + 1
```
<div style="text-align:center"><img src=`r file` width="70%" height="70%"/></div>
## Examples of `robvis` in published papers
* Perivoliotis, Konstantinos, et al. "[Comparing the efficacy and safety of laparoscopic and robotic adrenalectomy: a meta-analysis and trial sequential analysis.](https://link.springer.com/article/10.1007/s00423-020-01860-9)" Langenbeck's Archives of Surgery (2020): 1-11.
* Adile, Ashley A., et al. "[Salvage therapy for progressive, treatment-refractory or recurrent pediatric medulloblastoma: a systematic review protocol.](https://systematicreviewsjournal.biomedcentral.com/articles/10.1186/s13643-020-01307-8)" Systematic Reviews 9.1 (2020): 1-9.
* Tanneru, Karthik, et al. "[Meta-analysis and systematic review of intermediate-term follow-up of prostatic urethral lift for benign prostatic hyperplasia.](https://link.springer.com/article/10.1007/s11255-020-02408-y)" International Urology and Nephrology (2020): 1-10.
* Veloso, Andreia, et al.. "[Effectiveness of Cognitive Training for School-Aged Children and Adolescents With Attention Deficit/Hyperactivity Disorder: A Systematic Review.](https://www.frontiersin.org/articles/10.3389/fpsyg.2019.02983/full)" Frontiers in Psychology 10 (2020): 2983.
* Simillis, Constantinos, et al. "[Postoperative chemotherapy improves survival in patients with resected high‐risk stage II colorectal cancer: results of a systematic review and meta‐analysis.](https://onlinelibrary.wiley.com/doi/pdf/10.1111/codi.14994)" Colorectal Disease (2020).
* Habadi, Mohammed Ibrahim, et al. "[Prevalence of Panic Disorders in the Primary Health Care Setting: A Systematic Review and Meta-Analysis.](https://www.ecronicon.com/ecmi/pdf/prevalence-of-panic-disorders-in-the-primary-health-care-setting-a-systematic-review-and-meta-analysis.pdf)" EC Microbiology 16.1 (2019): 01-09.
* Gibb, Kate, et al. "[The consistent burden in published estimates of delirium occurrence in medical inpatients over four decades: a systematic review and meta-analysis study.](https://www.medrxiv.org/content/medrxiv/early/2019/08/29/19005165.full.pdf)" medRxiv (2019): 19005165.
See more [here](https://scholar.google.com/scholar?cites=12564214960529060925&as_sdt=2005&sciodt=0,5&hl=en).
## Code of conduct
Please note that the 'robvis' project is released with a
[Contributor Code of Conduct](https://github.com/mcguinlu/robvis/blob/master/CODE_OF_CONDUCT.md).
By contributing to this project, you agree to abide by its terms.
## License
This project is licensed under the MIT License - see the [LICENSE.md](https://github.com/mcguinlu/robvis/blob/master/LICENSE) file for details.
## Acknowledgments
* The `rob_summary()` function was based on code forwarded by a colleague. I recently discovered that this code was adapted from that presented in the wonderful "[Doing Meta-Analysis in R](https://bookdown.org/MathiasHarrer/Doing_Meta_Analysis_in_R/plotting-the-summary.html)" guide, so I would like to acknowledge the authors here.
* [Emily Kothe](https://github.com/ekothe) for help in fixing `ggplot2` coding issues.
* [Eliza Grames](https://github.com/elizagrames) for creating the `robvis` hex sticker.