ggcoxfunctional {survminer} | R Documentation |
Functional Form of Continuous Variable in Cox Proportional Hazards Model
Description
Displays graphs of continuous explanatory variable against martingale residuals of null
cox proportional hazards model, for each term in of the right side of formula
. This might help to properly
choose the functional form of continuous variable in cox model (coxph). Fitted lines with lowess function
should be linear to satisfy cox proportional hazards model assumptions.
Usage
ggcoxfunctional(
formula,
data = NULL,
fit,
iter = 0,
f = 0.6,
point.col = "red",
point.size = 1,
point.shape = 19,
point.alpha = 1,
xlim = NULL,
ylim = NULL,
ylab = "Martingale Residuals \nof Null Cox Model",
title = NULL,
caption = NULL,
ggtheme = theme_survminer(),
...
)
## S3 method for class 'ggcoxfunctional'
print(x, ..., newpage = TRUE)
Arguments
formula |
a formula object, with the response on the left of a ~ operator, and the terms on the right. The response must be a survival object as returned by the Surv function. |
data |
a |
fit |
an object of class coxph.object - created with coxph function. |
iter |
parameter of lowess. |
f |
parameter of lowess. |
point.col , point.size , point.shape , point.alpha |
color, size, shape and visibility to be used for points. |
xlim , ylim |
x and y axis limits e.g. xlim = c(0, 1000), ylim = c(0, 1). |
ylab |
y axis label. |
title |
the title of the final grob ( |
caption |
the caption of the final grob ( |
ggtheme |
function, ggplot2 theme name.
Allowed values include ggplot2 official themes: see |
... |
further arguments passed to the function |
x |
an object of class ggcoxfunctional |
newpage |
open a new page. See |
Value
Returns an object of class ggcoxfunctional
which is a list of ggplots.
Functions
-
ggcoxfunctional
: Functional Form of Continuous Variable in Cox Proportional Hazards Model.
Author(s)
Marcin Kosinski , m.p.kosinski@gmail.com
Examples
library(survival)
data(mgus)
res.cox <- coxph(Surv(futime, death) ~ mspike + log(mspike) + I(mspike^2) +
age + I(log(age)^2) + I(sqrt(age)), data = mgus)
ggcoxfunctional(res.cox, data = mgus, point.col = "blue", point.alpha = 0.5)
ggcoxfunctional(res.cox, data = mgus, point.col = "blue", point.alpha = 0.5,
title = "Pass the title", caption = "Pass the caption")