plotprog.msm: Kaplan Meier estimates of incidence

In msm: Multi-State Markov and Hidden Markov Models in Continuous Time

Kaplan Meier estimates of incidence

Description

Compute and plot Kaplan-Meier estimates of the probability that each successive state has not occurred yet.

Usage

plotprog.msm(
  formula,
  subject,
  data,
  legend.pos = NULL,
  xlab = "Time",
  ylab = "1 - incidence probability",
  lwd = 1,
  xlim = NULL,
  mark.time = TRUE,
  ...
)

Arguments

formula	A formula giving the vectors containing the observed states and the corresponding observation times. For example, state ~ time Observed states should be in the set 1, ...{}, n, where n is the number of states.
subject	Vector of subject identification numbers for the data specified by formula. If missing, then all observations are assumed to be on the same subject. These must be sorted so that all observations on the same subject are adjacent.
data	An optional data frame in which the variables represented by state, time and subject can be found.
legend.pos	Vector of the x and y position, respectively, of the legend.
xlab	x axis label.
ylab	y axis label.
lwd	Line width. See par.
xlim	x axis limits, e.g. c(0,10) for an axis ranging from 0 to 10. Default is the range of observation times.
mark.time	Mark the empirical survival curve at each censoring point, see lines.survfit.
...	Other arguments to be passed to the plot and lines.survfit functions.

Details

If the data represent observations of the process at arbitrary times, then the first occurrence of the state in the data will usually be greater than the actual first transition time to that state. Therefore the probabilities plotted by plotprog.msm will be overestimates.

See Also

survfit, plot.survfit

msm documentation built on Oct. 5, 2024, 1:07 a.m.