epiR (version 1.0-15)

epi.insthaz: Event instantaneous hazard based on Kaplan-Meier survival estimates

Description

Compute event instantaneous hazard on the basis of a Kaplan-Meier survival function.

Usage

epi.insthaz(survfit.obj, conf.level = 0.95)

Arguments

survfit.obj

a survfit object, computed using the survival package.

conf.level

magnitude of the returned confidence interval. Must be a single number between 0 and 1.

Value

A data frame with three or four elements: strata the strata identifier, time the observed failure times, est the proportion of the population experiencing the event of interest per unit time, lower the lower bound of the confidence interval of the proportion of the population experiencing the event of interest per unit time, and upper the upper bound of the confidence interval of the proportion of the population experiencing the event of interest per unit time.

Details

Computes the instantaneous hazard of the event of interest, equivalent to the proportion of the population failing per unit time.

References

Venables W, Ripley B (2002). Modern Applied Statistics with S, fourth edition. Springer, New York, pp. 353 - 385.

Singer J, Willett J (2003). Applied Longitudinal Data Analysis Modeling Change and Event Occurrence. Oxford University Press, London, pp. 348.

Examples

# NOT RUN {
library(survival)
dat <- lung

dat$status <- ifelse(dat$status == 1, 0, dat$status)
dat$status <- ifelse(dat$status == 2, 1, dat$status)
dat$sex <- factor(dat$sex, levels = c(1,2), labels = c("Male","Female"))

lung.km01 <- survfit(Surv(time = time, event = status) ~ 1, data = dat)
lung.haz01 <- epi.insthaz(lung.km01, conf.level = 0.95)

lung.shaz01 <- data.frame(
  time = lowess(lung.haz01$time, lung.haz01$lower, f = 0.20)$x,
  est =  lowess(lung.haz01$time, lung.haz01$est, f = 0.20)$y,
  low =  lowess(lung.haz01$time, lung.haz01$lower, f = 0.20)$y,
  upp =  lowess(lung.haz01$time, lung.haz01$upper, f = 0.20)$y)

plot(x = lung.haz01$time, y = lung.haz01$est, xlab = "Time (days)", 
   ylab = "Daily probability of event", type = "s", 
   col = "grey", ylim = c(0, 0.05))
lines(x = lung.shaz01$time, y = lung.shaz01$est, 
      lty = 1, lwd = 2, col = "black")
lines(x = lung.shaz01$time, y = lung.shaz01$low, 
      lty = 2, lwd = 1, col = "black")
lines(x = lung.shaz01$time, y = lung.shaz01$upp, 
      lty = 2, lwd = 1, col = "black")

# }
# NOT RUN {
library(ggplot2)

ggplot() +
  theme_bw() +
  geom_step(data = lung.haz01, aes(x = time, y = est), colour = "grey") + 
  geom_smooth(data = lung.haz01, aes(x = time, y = est), method = "loess", 
     colour = "black", size = 0.75, linetype = "solid", 
     se = FALSE, span = 0.20) +
  geom_smooth(data = lung.haz01, aes(x = time, y = lower), method = "loess", 
     colour = "black", size = 0.5, linetype = "dashed", 
     se = FALSE, span = 0.20) +
  geom_smooth(data = lung.haz01, aes(x = time, y = upper), method = "loess", 
     colour = "black", size = 0.5, linetype = "dashed", 
     se = FALSE, span = 0.20) +
  scale_x_continuous(limits = c(0,1000), name = "Time (days)") +
  scale_y_continuous(limits = c(0,0.05), name = "Daily probability of event") 
# }
# NOT RUN {
## Stratify by gender:

lung.km02 <- survfit(Surv(time = time, event = status) ~ sex, data = dat)
lung.haz02 <- epi.insthaz(lung.km02, conf.level = 0.95)

# }
# NOT RUN {
library(ggplot2)

ggplot() +
  theme_bw() +
  geom_step(data = lung.haz02, aes(x = time, y = est), colour = "grey") + 
  facet_grid(strata ~ .) +
  geom_smooth(data = lung.haz02, aes(x = time, y = est), method = "loess", 
     colour = "black", size = 0.75, linetype = "solid", 
     se = FALSE, span = 0.20) +
  geom_smooth(data = lung.haz02, aes(x = time, y = lower), method = "loess", 
     colour = "black", size = 0.5, linetype = "dashed", 
     se = FALSE, span = 0.20) +
  geom_smooth(data = lung.haz02, aes(x = time, y = upper), method = "loess", 
     colour = "black", size = 0.5, linetype = "dashed", 
     se = FALSE, span = 0.20) +
  scale_x_continuous(limits = c(0,1000), name = "Time (days)") +
  scale_y_continuous(limits = c(0,0.05), name = "Daily probability of event")
# }