Is your feature request related to a problem? Please describe.
I am currently trying to merge uni- and multivariate regression results from 6 "predictor" variables in the same forest plot using plot_summs, so I can visually summarize the individual regression of a parameter compared to a multivariate analysis.
While I know that I can set up 6 univariate functions and 1 multivariate function (with lm...) and plot them, this runs into issues when trying to set up a legend that summarizes all "univariate" into one legend item (next to the "multivariate" item). I tried several workarounds with scale_color_manual ( breaks (...)) that achieve a manual creation of a "univariate" and "multivariate" item, however, then there is still a default mode of variables (Model 1, Model 2, Model 3 ..., Model 7) that I cannot remove.
Describe the solution you'd like
Option 1 (preferred): Implement the Option to summarize a group of lm models into one group corresponding to one legend item
Option 2: Implement an option to manually decide on the legend items to be shown
Option 3: suggestion how I can fix the described problem when using the scale_color_manual function, that the default legend items (Model 1 ...) still shows up and cannot be removed
Describe any alternatives or other implementations that you might know of
See above.
Additional context
Example code on the problem, how I tried to fix it:
Load necessary libraries
library(jtools)
library(ggplot2)
Example of linear regression models
fit1 <- lm(mpg ~ wt + hp + qsec, data = mtcars)
fit2 <- lm(mpg ~ wt + hp, data = mtcars)
Is your feature request related to a problem? Please describe. I am currently trying to merge uni- and multivariate regression results from 6 "predictor" variables in the same forest plot using plot_summs, so I can visually summarize the individual regression of a parameter compared to a multivariate analysis.
While I know that I can set up 6 univariate functions and 1 multivariate function (with lm...) and plot them, this runs into issues when trying to set up a legend that summarizes all "univariate" into one legend item (next to the "multivariate" item). I tried several workarounds with scale_color_manual ( breaks (...)) that achieve a manual creation of a "univariate" and "multivariate" item, however, then there is still a default mode of variables (Model 1, Model 2, Model 3 ..., Model 7) that I cannot remove.
Describe the solution you'd like Option 1 (preferred): Implement the Option to summarize a group of lm models into one group corresponding to one legend item Option 2: Implement an option to manually decide on the legend items to be shown Option 3: suggestion how I can fix the described problem when using the scale_color_manual function, that the default legend items (Model 1 ...) still shows up and cannot be removed
Describe any alternatives or other implementations that you might know of See above.
Additional context Example code on the problem, how I tried to fix it:
Load necessary libraries
library(jtools) library(ggplot2)
Example of linear regression models
fit1 <- lm(mpg ~ wt + hp + qsec, data = mtcars) fit2 <- lm(mpg ~ wt + hp, data = mtcars)
Create the plot_summs plot without the legend
p <- plot_summs(fit1, fit2, model.names = c("fit1", "fit2"), colors = c("blue", "red")) + theme(legend.position = "none") # Remove default legend
Add the custom legend
p <- p + scale_color_manual( name = "Models", # Name of the legend breaks = c("fit1", "fit2"), values = c("fit1" = "blue", "fit2" = "red"), # Adjust colors as needed labels = c("f1", "f2") # Adjust labels as needed ) + guides(color = guide_legend(override.aes = list(linetype = c(1, 1), shape = c(16, 16))))
Position the custom legend
p <- p + theme(legend.position = "right")
print(p)