psa.plot: Graphical depiction of the probabilistic sensitivity analysis...

In expertsurv: Incorporate Expert Opinion with Parametric Survival Models

Graphical depiction of the probabilistic sensitivity analysis for the survival curves - ported from survHE

Description

Plots the survival curves for all the PSA simulations. The function is actually deprecated - similar graphs can be obtained directly using the plot method (with options), which allows a finer depiction of the results.

Usage

psa.plot(psa, ...)

Arguments

psa	the result of the call to the function make.surv
...	Optional graphical parameters, such as: xlab = label for the x-axis ylab = label for the y-axis col = (vector) of colors for the lines to be plotted alpha = the level of transparency for the curves (default = 0.2)

Value

ggplot2 object of the survival curve including parameter uncertainty

Author(s)

Gianluca Baio

References

\insertRef

Baio.2020expertsurv

Examples

require("dplyr")
param_expert_example1 <- list()
param_expert_example1[[1]] <- data.frame(dist = c("norm","t"),
                                        wi = c(0.5,0.5), # Ensure Weights sum to 1
                                        param1 = c(0.1,0.12),
                                        param2 = c(0.15,0.5),
                                        param3 = c(NA,3))

timepoint_expert <- 14
data2 <- data %>% rename(status = censored) %>% mutate(time2 = ifelse(time > 10, 10, time),
                                                      status2 = ifelse(time> 10, 0, status))
example1 <- fit.models.expert(formula=Surv(time2,status2)~1,data=data2,
                             distr=c("wph", "gomp"),
                             method="mle",
                             pool_type = "log pool",
                             opinion_type = "survival",
                             times_expert = timepoint_expert,
                             param_expert = param_expert_example1)

p.mle = make.surv(example1,mod= 2,t = 1:30, nsim=1000) #Plot the Gompertz model
psa.plot(p.mle , name_labs = "PSA", labs = "Gompertz", col ="blue")

expertsurv documentation built on Oct. 5, 2023, 5:09 p.m.