plot.standsurv: Plot standardized metrics from a fitted flexsurv model

In flexsurv: Flexible Parametric Survival and Multi-State Models

Plot standardized metrics from a fitted flexsurv model

Description

Plot standardized metrics such as the marginal survival, restricted mean survival and hazard, based on a fitted flexsurv model.

Usage

## S3 method for class 'standsurv'
plot(x, contrast = FALSE, ci = FALSE, expected = FALSE, ...)

Arguments

x	A standsurv object returned by standsurv
contrast	Should contrasts of standardized metrics be plotted. Defaults to FALSE
ci	Should confidence intervals be plotted (if calculated in standsurv)?
expected	Should the marginal expected survival / hazard also be plotted? This can only be invoked if rmap and ratetable have been passed to standsurv
...	Not currently used

Value

A ggplot showing the standardized metric calculated by standsurv over time. Modification of the plot is possible by adding further ggplot objects, see Examples.

Examples

## Use bc dataset, with an age variable appended
## mean age is higher in those with smaller observed survival times 
newbc <- bc
newbc$age <- rnorm(dim(bc)[1], mean = 65-scale(newbc$recyrs, scale=FALSE), 
sd = 5)

## Fit a Weibull flexsurv model with group and age as covariates
weib_age <- flexsurvreg(Surv(recyrs, censrec) ~ group+age, data=newbc,
                       dist="weibull")
## Calculate standardized survival and the difference in standardized survival
## for the three levels of group across a grid of survival times
standsurv_weib_age <- standsurv(weib_age,
                                           at = list(list(group="Good"),
                                                     list(group="Medium"),
                                                     list(group="Poor")),
                                           t=seq(0,7, length=100),
                                           contrast = "difference", ci=TRUE,
                                           boot = TRUE, B=10, seed=123)
plot(standsurv_weib_age)
plot(standsurv_weib_age) + ggplot2::theme_bw() + ggplot2::ylab("Survival") +
 ggplot2::xlab("Time (years)") + 
 ggplot2::guides(color=ggplot2::guide_legend(title="Prognosis"),
                               fill=ggplot2::guide_legend(title="Prognosis"))
plot(standsurv_weib_age, contrast=TRUE, ci=TRUE) + 
 ggplot2::ylab("Difference in survival") 

flexsurv documentation built on Feb. 16, 2023, 5:07 p.m.