expertsurv (version 1.4.1)

psa.plot: 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, ...)

Value

ggplot2 object of the survival curve including parameter uncertainty

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)

Author

Gianluca Baio

References

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")