plot_surv_lines {contsurvplot} | R Documentation |

## Plot Individual Survival Curves or CIFs for Specific Values of a Continuous Covariate

### Description

Using a previously fit time-to-event model, this function plots survival curves or CIFs that would have been observed if every individual in the dataset had been set to specific values of a continuous covariate.

### Usage

```
plot_surv_lines(time, status, variable, group=NULL,
data, model, cif=FALSE, conf_int=FALSE,
conf_level=0.95, n_boot=300,
na.action=options()$na.action,
horizon=NULL, fixed_t=NULL, max_t=Inf,
discrete=TRUE, custom_colors=NULL,
start_color="blue", end_color="red",
size=1, linetype="solid", alpha=1,
xlab="Time", ylab="Survival Probability",
title=NULL, subtitle=NULL,
legend.title=variable, legend.position="right",
gg_theme=ggplot2::theme_bw(),
facet_args=list(), ci_alpha=0.4,
kaplan_meier=FALSE, km_size=0.5,
km_linetype="solid", km_alpha=1,
km_color="black", km_ci=FALSE,
km_ci_type="plain", km_ci_level=0.95,
km_ci_alpha=0.4, ...)
```

### Arguments

`time` |
A single character string specifying the time-to-event variable. Needs to be a valid column name of a numeric variable in |

`status` |
A single character string specifying the status variable, indicating if a person has experienced an event or not. Needs to be a valid column name of a numeric or logical variable in |

`variable` |
A single character string specifying the continuous variable of interest, for which the survival curves should be estimated. This variable has to be contained in the |

`group` |
An optional single character string specifying a factor variable in |

`data` |
A |

`model` |
A model describing the time-to-event process (such as an |

`cif` |
Whether to plot the cumulative incidence (CIF) instead of the survival probability. If multiple failure types are present, the survival probability cannot be estimated in an unbiased way. This function will always return CIF estimates in that case. |

`conf_int` |
Whether to plot point-wise bootstrap confidence intervals or not. |

`conf_level` |
A number specifying the confidence level of the bootstrap confidence intervals. Ignored if |

`n_boot` |
A single integer specifying how many bootstrap repetitions should be performed. Ignored if |

`na.action` |
How missing values should be handled. Can be one of: |

`horizon` |
A numeric vector containing a range of values of |

`fixed_t` |
A numeric vector containing points in time at which the survival probabilities should be calculated or |

`max_t` |
A number indicating the latest survival time which is to be plotted. |

`discrete` |
Whether to use a continuous color scale or a discrete one (default). If |

`custom_colors` |
An optional character vector of colors to use when |

`start_color` |
The color used for the lowest value in |

`end_color` |
The color used for the highest value in |

`size` |
A single number specifying the size of the drawn curves. |

`linetype` |
A single character string specifying the linetype of the curves. |

`alpha` |
The transparency level of the plot. |

`xlab` |
A character string used as the x-axis label of the plot. |

`ylab` |
A character string used as the y-axis label of the plot. |

`title` |
A character string used as the title of the plot. |

`subtitle` |
A character string used as the subtitle of the plot. |

`legend.title` |
A character string used as the legend title of the plot. |

`legend.position` |
Where to put the legend. See |

`gg_theme` |
A ggplot2 theme which is applied to the plot. |

`facet_args` |
A named list of arguments that are passed to the |

`ci_alpha` |
A single number defining the transparency level of the confidence interval bands. |

`kaplan_meier` |
Whether to add a standard Kaplan-Meier estimator to the plot or not. If |

`km_size` |
The size of the Kaplan-Meier line. Ignored if |

`km_linetype` |
The linetype of the Kaplan-Meier line. Ignored if |

`km_alpha` |
The transparency level of the Kaplan-Meier line. Ignored if |

`km_color` |
The color of the Kaplan-Meier line. Ignored if |

`km_ci` |
Whether to draw a confidence interval around the Kaplan-Meier estimates. Ignored if |

`km_ci_type` |
Which type of confidence interval to calculate for the Kaplan-Meier estimates. Corresponds to the |

`km_ci_level` |
Which confidence level to use for the confidence interval of the Kaplan-Meier estimates. Ignored if |

`km_ci_alpha` |
The transparency level of the confidence interval of the Kaplan-Meier estimates. Ignored if |

`...` |
Further arguments passed to |

### Details

A simple plot of multiple covariate-specific survival curves. Internally, it uses the `curve_cont`

function to calculate the survival curves.

### Value

Returns a `ggplot2`

object.

### Author(s)

Robin Denz

### Examples

```
library(contsurvplot)
library(riskRegression)
library(survival)
library(ggplot2)
library(splines)
# using data from the survival package
data(nafld, package="survival")
# take a random sample to keep example fast
set.seed(42)
nafld1 <- nafld1[sample(nrow(nafld1), 150), ]
# fit cox-model with age
model <- coxph(Surv(futime, status) ~ age, data=nafld1, x=TRUE)
# plot effect of age on survival using defaults
plot_surv_lines(time="futime",
status="status",
variable="age",
data=nafld1,
model=model)
# plot it only for some specific user-defined values
plot_surv_lines(time="futime",
status="status",
variable="age",
data=nafld1,
model=model,
horizon=c(40, 52, 63, 81))
## showing non-linear effects
# fit cox-model with bmi modelled using B-Splines,
# adjusting for age and sex
model2 <- coxph(Surv(futime, status) ~ age + male + bs(bmi, df=3),
data=nafld1, x=TRUE)
# plot effect of bmi on survival
plot_surv_lines(time="futime",
status="status",
variable="bmi",
data=nafld1,
model=model2,
horizon=c(20, 30, 40))
```

*contsurvplot*version 0.2.1 Index]