survrec.R
In survrec: Survival Analysis for Recurrent Event Data

## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE, comment = "#>", message = FALSE,
  warning = FALSE, fig.width = 6.2, fig.height = 5,
  fig.align = "center"
)
set.seed(1)

## ----load---------------------------------------------------------------------
library(survrec)

## ----data-mmc-----------------------------------------------------------------
data(MMC)
head(MMC)

## ----data-colon---------------------------------------------------------------
data(colon)
head(colon)

## ----survr--------------------------------------------------------------------
x <- Survr(MMC$id, MMC$time, MMC$event)

## ----fit-basic----------------------------------------------------------------
fit <- survfitr(Survr(id, time, event) ~ 1, data = MMC, type = "wang-chang")
fit

## ----quantiles----------------------------------------------------------------
quantile(fit, probs = c(0.25, 0.5, 0.75))

## ----autoplot-basic, fig.cap = "Wang-Chang estimate of the MMC gap-time survival."----
autoplot(fit)

## ----estimators, fig.cap = "The three estimators on the MMC data."------------
plotEstimators(x)

## ----frailty------------------------------------------------------------------
mle <- mlefrailty_fit(x, alpha.console = FALSE)
mle$alpha

## ----frailties----------------------------------------------------------------
round(mle$frailties, 3)

## ----colon-fit, fig.cap = "PSH estimates of the rehospitalization gap times by Dukes stage."----
fit.dukes <- survfitr(Survr(hc, time, event) ~ as.factor(dukes),
  data = colon, type = "pena"
)
autoplot(fit.dukes)

## ----tidy---------------------------------------------------------------------
head(as.data.frame(fit.dukes))

## ----mcf, fig.cap = "Mean cumulative number of rehospitalizations by Dukes stage."----
autoplot(mcf(Survr(hc, time, event) ~ as.factor(dukes), data = colon))

## ----survdiffr----------------------------------------------------------------
b <- survdiffr(Survr(hc, time, event) ~ as.factor(dukes),
  data = colon, q = 0.5, B = 199, boot.F = "WC", seed = 2026
)

## ----survdiffr-summary--------------------------------------------------------
summary(b)

## ----survdiffr-plot, fig.cap = "Bootstrap distributions of the median rehospitalization-free time."----
autoplot(b)

## ----bootci-------------------------------------------------------------------
boot::boot.ci(b$"1", type = c("norm", "basic", "perc"))

## ----session------------------------------------------------------------------
sessionInfo()