ggcoxdiagnostics | R Documentation |
Displays diagnostics graphs presenting goodness of Cox Proportional Hazards Model fit, that can be calculated with coxph function.
ggcoxdiagnostics(
fit,
type = c("martingale", "deviance", "score", "schoenfeld", "dfbeta", "dfbetas",
"scaledsch", "partial"),
...,
linear.predictions = type %in% c("martingale", "deviance"),
ox.scale = ifelse(linear.predictions, "linear.predictions", "observation.id"),
hline = TRUE,
sline = TRUE,
sline.se = TRUE,
hline.col = "red",
hline.size = 1,
hline.alpha = 1,
hline.yintercept = 0,
hline.lty = "dashed",
sline.col = "blue",
sline.size = 1,
sline.alpha = 0.3,
sline.lty = "dashed",
point.col = "black",
point.size = 1,
point.shape = 19,
point.alpha = 1,
title = NULL,
subtitle = NULL,
caption = NULL,
ggtheme = ggplot2::theme_bw()
)
fit |
an object of class coxph.object - created with coxph function. |
type |
the type of residuals to present on Y axis of a diagnostic plot.
The same as in residuals.coxph: character string indicating the type of
residual desired. Possible values are |
... |
further arguments passed to |
linear.predictions |
(deprecated, see |
ox.scale |
one value from |
hline |
a logical - should the horizontal line be added to highlight the |
sline , sline.se |
a logical - should the smooth line be added to highlight the local average for residuals. |
hline.col , hline.size , hline.lty , hline.alpha , hline.yintercept |
color, size, linetype, visibility and Y-axis coordinate to be used for geom_hline.
Used only when |
sline.col , sline.size , sline.lty , sline.alpha |
color, size, linetype and visibility to be used for geom_smooth.
Used only when |
point.col , point.size , point.shape , point.alpha |
color, size, shape and visibility to be used for points. |
title , subtitle , caption |
main title, subtitle and caption. |
ggtheme |
function, ggplot2 theme name. Default value is ggplot2::theme_bw().
Allowed values include ggplot2 official themes: see |
Returns an object of class ggplot
.
ggcoxdiagnostics()
: Diagnostic Plots for Cox Proportional Hazards Model with ggplot2
Marcin Kosinski , m.p.kosinski@gmail.com
library(survival)
coxph.fit2 <- coxph(Surv(futime, fustat) ~ age + ecog.ps, data=ovarian)
ggcoxdiagnostics(coxph.fit2, type = "deviance")
ggcoxdiagnostics(coxph.fit2, type = "schoenfeld", title = "Diagnostic plot")
ggcoxdiagnostics(coxph.fit2, type = "deviance", ox.scale = "time")
ggcoxdiagnostics(coxph.fit2, type = "schoenfeld", ox.scale = "time",
title = "Diagnostic plot", subtitle = "Data comes from survey XYZ",
font.subtitle = 9)
ggcoxdiagnostics(coxph.fit2, type = "deviance", ox.scale = "linear.predictions",
caption = "Code is available here - link", font.caption = 10)
ggcoxdiagnostics(coxph.fit2, type = "schoenfeld", ox.scale = "observation.id")
ggcoxdiagnostics(coxph.fit2, type = "scaledsch", ox.scale = "time")
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.