Visualize 'Confounder' Control in Meta-Analyses
Count and plot non-confounders
Facet by constructs
Add Cochrane-style symbols to heatmaps and traffic light plots
IPI data
Label values using ROBINS approach
Launch metaconfoundr Shiny app
Tidy metaconfoundr data layouts
Plot a heatmap or traffic light plot of metaconfoundr() summaries
Prepare a meta-analysis data set for metaconfoundr
metaconfoundr: Visualize Confounder Control in Meta-Analyses
Pipe operator
Objects exported from other packages
Add Cochrane-style palettes to ggplots
Add a score of confounding control
Summarize the control quality of studies
A minimal theme for metaconfoundr plots
Visualize 'confounder' control in meta-analysis. 'metaconfoundr' is an approach to evaluating bias in studies used in meta-analyses based on the causal inference framework. Study groups create a causal diagram displaying their assumptions about the scientific question. From this, they develop a list of important 'confounders'. Then, they evaluate whether studies controlled for these variables well. 'metaconfoundr' is a toolkit to facilitate this process and visualize the results as heat maps, traffic light plots, and more.
Useful links