(R) 为绘图添加置信区间

Question

I am using R. I am following this tutorial over here (https://rviews.rstudio.com/2017/09/25/survival-analysis-with-r/ ) and I am trying to adapt the code for a similar problem.

In this tutorial, a statistical model is developed on a dataset and then this statistical model is used to predict 3 news observations. We then plot the results for these 3 observations:

#load libraries
library(survival)

library(dplyr)

library(ranger)

library(data.table)

library(ggplot2)

#use the built in "lung" data set
#remove missing values (dataset is called "a")

a = na.omit(lung)

#create id variable

a$ID <- seq_along(a[,1])

#create test set with only the first 3 rows

new = a[1:3,]

#create a training set by removing first three rows

a = a[-c(1:3),]



#fit survival model (random survival forest)

r_fit <- ranger(Surv(time,status) ~ age + sex + ph.ecog + ph.karno + pat.karno + meal.cal + wt.loss, data = a, mtry = 4, importance = "permutation", splitrule = "extratrees", verbose = TRUE)

#create new intermediate variables required for the survival curves

death_times <- r_fit$unique.death.times

surv_prob <-data.frame(r_fit$survival)

avg_prob <- sapply(surv_prob, mean)

#use survival model to produce estimated survival curves for the first three observations

pred <- predict(r_fit, new, type = 'response')$survival

pred <- data.table(pred)

colnames(pred) <- as.character(r_fit$unique.death.times)

#plot the results for these 3 patients

plot(r_fit$unique.death.times, pred[1,], type = "l", col = "red")

lines(r_fit$unique.death.times, r_fit$survival[2,], type = "l", col = "green")

lines(r_fit$unique.death.times, r_fit$survival[3,], type = "l", col = "blue")

From here, I would like to try an add confidence interval (confidence regions) to each of these 3 curves, so that they look something like this:

I found a previous stackoverflow post ( survfit() Shade 95% confidence interval survival plot ) that shows how to do something similar, but I am not sure how to extend the results from this post to each individual observation.

Does anyone know if there is a direct way to add these confidence intervals?

Thanks

Answer 1

If you create your plot using ggplot , you can use the geom_ribbon function to draw confidence intervals as follows:

    ggplot(data=...)+
    geom_line(aes(x=..., y=...),color=...)+
    geom_ribbon(aes(x=.. ,ymin =.., ymax =..), fill=.. , alpha =.. )+
    geom_line(aes(x=..., y=...),color=...)+
    geom_ribbon(aes(x=.. ,ymin =.., ymax =..), fill=.. , alpha =.. )
    

You can put + after geom_line and repeat the same steps for each observation. You can also check: Having trouble plotting multiple data sets and their confidence intervals on the same GGplot. Data Frame included and https://bookdown.org/ripberjt/labbook/appendix-guide-to-data-visualization.html