UPDATE: robvis now exists as a
web-app, aimed at those who are
not familiar with R or who want to explore the package’s functionality
before installing it locally.
The robvis package takes the summary table from risk-of-bias
assessments and produces plots formatted according to the assessment
tool used.
Install the CRAN version:
install.packages("robvis")Alternatively, the development version can be installed using:
install.packages("devtools")
devtools::install_github("mcguinlu/robvis")To update the package, run the install_github("mcguinlu/robvis")
command again.
To load your own data from a .csv file:
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),
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.
The package contains two plotting functions:
Returns a ggplot object displaying a weighted barchart of the risk of bias of included studies across the domains of the specified tool.
summary_rob <- rob_summary(data = data_rob2, tool = "ROB2")
summary_robReturns a ggplot object displaying a “traffic light plot”, displaying the risk of bias judgment in each domain for each study.
trafficlight_rob <- rob_traffic_light(data = data_rob2, tool = "ROB2")
trafficlight_robOutputs 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).
rob_tools()
[1] "ROB2"
[1] "ROBINS-I"
[1] "QUADAS-2"
[1] "ROB1"
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:
summary_rob <- rob_summary(data = data_rob2, tool = "ROB2", colour = "colourblind")
summary_robAnd to define your own colour scheme:
summary_rob <- rob_summary(data = data_rob2, tool = "ROB2", colour = c("#f442c8","#bef441","#000000"))
summary_robBy default, the rob_summary() function creates a barplot weighted by
some measure of a study’s precision. This can be prevented using the
“weighted” argument. For example, compare the following two plots:
summary_rob <- rob_summary(data = data_rob2, tool = "ROB2")
summary_robsummary_rob <- rob_summary(data = data_rob2, tool = "ROB2", weighted = FALSE)
summary_robFinally, 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 to the unweighted RoB2.0 plot created above:
library(ggplot2)
summary_rob +
ggtitle("Summary of RoB2.0 assessments")- Perivoliotis, Konstantinos, et al. “Comparing the efficacy and safety of laparoscopic and robotic adrenalectomy: a meta-analysis and trial sequential analysis.” 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.” 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.” 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.” 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.” Colorectal Disease (2020).
- Habadi, Mohammed Ibrahim, et al. “Prevalence of Panic Disorders in the Primary Health Care Setting: A Systematic Review and Meta-Analysis.” 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.” medRxiv (2019): 19005165.
Please note that the ‘robvis’ project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
This project is licensed under the MIT License - see the LICENSE.md file for details.
- 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” guide, so I would like to acknowledge the authors here. - Emily Kothe for help in fixing
ggplot2coding issues. - Eliza Grames for creating the
robvishex sticker.