regression_forest {clinpubr} | R Documentation |
Forest plot of regression results
Description
Generate the forest plot of logistic or Cox regression with different models.
Usage
regression_forest(
data,
model_vars,
y,
time = NULL,
as_univariate = FALSE,
est_nsmall = 2,
p_nsmall = 3,
show_vars = NULL,
save_plot = FALSE,
filename = NULL,
...
)
Arguments
data |
A data frame. |
model_vars |
A character vector or a named list of predictor variables for different models. |
y |
A character string of the outcome variable. |
time |
A character string of the time variable. If |
as_univariate |
A logical value indicating whether to treat the model_vars as univariate. |
est_nsmall |
An integer specifying the precision for the estimates in the plot. |
p_nsmall |
An integer specifying the number of decimal places for the p-values. |
show_vars |
A character vector of variable names to be shown in the plot. If |
save_plot |
A logical value indicating whether to save the plot. |
filename |
A character string specifying the filename for the plot. If |
... |
Additional arguments passed to the |
Value
A gtable
object.
Examples
data(cancer, package = "survival")
cancer$ph.ecog_cat <- factor(cancer$ph.ecog, levels = c(0:3), labels = c("0", "1", ">=2", ">=2"))
regression_forest(cancer,
model_vars = c("age", "sex", "wt.loss", "ph.ecog_cat", "meal.cal"), y = "status", time = "time",
as_univariate = TRUE, save_plot = FALSE
)
regression_forest(cancer,
model_vars = c("age", "sex", "wt.loss", "ph.ecog_cat", "meal.cal"), y = "status", time = "time",
show_vars = c("age", "sex", "ph.ecog_cat", "meal.cal"), save_plot = FALSE
)
regression_forest(cancer,
model_vars = list(
M0 = c("age"),
M1 = c("age", "sex", "wt.loss", "ph.ecog_cat", "meal.cal"),
M2 = c("age", "sex", "wt.loss", "ph.ecog_cat", "meal.cal", "pat.karno")
),
y = "status", time = "time",
show_vars = c("age", "sex", "ph.ecog_cat", "meal.cal"), save_plot = FALSE
)