psa.plot {expertsurv} | R Documentation |
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 |
... |
Optional graphical parameters, such as: |
Value
ggplot2 object of the survival curve including parameter uncertainty
Author(s)
Gianluca Baio
References
Baio G (2020). “survHE: Survival Analysis for Health Economic Evaluation and Cost-Effectiveness Modeling.” Journal of Statistical Software, 95(14), 1–47. doi:10.18637/jss.v095.i14.
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")
[Package expertsurv version 1.4.0 Index]