ggcoxdiagnostics: Diagnostic Plots for Cox Proportional Hazards Model with...

In kassambara/survminer: Drawing Survival Curves using 'ggplot2'

Diagnostic Plots for Cox Proportional Hazards Model with ggplot2

Description

Displays diagnostics graphs presenting goodness of Cox Proportional Hazards Model fit, that can be calculated with coxph function.

Usage

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()
)

Arguments

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 "martingale", "deviance", "score", "schoenfeld", "dfbeta", "dfbetas" and "scaledsch". Only enough of the string to determine a unique match is required.
...	further arguments passed to residuals.coxph or to the function ggpar for customizing the plot.
linear.predictions	(deprecated, see ox.scale) a logical value indicating whether to show linear predictions for observations (TRUE) or just indexed of observations (FALSE) on X axis.
ox.scale	one value from c("linear.predictions", "observation.id", "time"). It defines what will be presented on OX scale. Possible values: y hat for "linear.predictions", Id of an observation for "observation.id" or Time for "time".
hline	a logical - should the horizontal line be added to highlight the Y=0 level.
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 hline = TRUE.
sline.col, sline.size, sline.lty, sline.alpha	color, size, linetype and visibility to be used for geom_smooth. Used only when sline = TRUE.
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 theme.

Value

Returns an object of class ggplot.

Functions

• ggcoxdiagnostics: Diagnostic Plots for Cox Proportional Hazards Model with ggplot2

Author(s)

Marcin Kosinski , [e-mail]

Examples

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")

kassambara/survminer documentation built on Feb. 15, 2023, 4:11 a.m.