interaction_plot {clinpubr} | R Documentation |
Plot interactions
Description
Plot interactions between variables. Both logistic and Cox proportional hazards regression models are supported. The predictor variables in the model are can be used both in linear form or in restricted cubic spline form.
Usage
interaction_plot(
data,
y,
predictor,
group_var,
time = NULL,
covars = NULL,
group_colors = NULL,
save_plot = FALSE,
filename = NULL,
height = 4,
width = 4,
xlab = predictor,
ylab = NULL,
show_n = TRUE,
group_title = group_var,
...
)
Arguments
data |
A data frame. |
y |
A character string of the outcome variable. |
predictor |
A character string of the predictor variable. |
group_var |
A character string of the group variable. The variable should be categorical. If a numeric variable is provided, it will be split by the median value. |
time |
A character string of the time variable. If |
covars |
A character vector of covariate names. |
group_colors |
A character vector of colors for the plot. If |
save_plot |
A logical value indicating whether to save the plot. |
filename |
The name of the file to save the plot. Support both |
height |
The height of the saved plot. |
width |
The width of the saved plot. |
xlab |
The label of the x-axis. |
ylab |
The label of the y-axis. |
show_n |
A logical value indicating whether to show the number of observations in the plot. |
group_title |
The title of the group variable. |
... |
Additional arguments passed to the |
Value
A ggplot
object.
Examples
data(cancer, package = "survival")
interaction_plot(cancer,
y = "status", time = "time", predictor = "age", group_var = "sex",
save_plot = FALSE
)
interaction_plot(cancer,
y = "status", predictor = "age", group_var = "sex",
save_plot = FALSE
)
interaction_plot(cancer,
y = "wt.loss", predictor = "age", group_var = "sex",
save_plot = FALSE
)