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

ggcoxdiagnostics {survminer} | R Documentation

## 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 , m.p.kosinski@gmail.com

### 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")

[Package survminer version 0.4.1 Index]