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msm (version 1.5)

plot.survfit.msm: Plot empirical and fitted survival curves

Description

Plot a Kaplan-Meier estimate of the survival probability and compare it with the fitted survival probability from a msm model.

Usage

## S3 method for class 'survfit.msm':
plot(x, from=1, to=NULL, range=NULL, covariates="mean",
                 interp=c("start","midpoint"), ci=c("none","normal","bootstrap"), B=100,
                 legend.pos=NULL, xlab="Time", ylab="Survival probability",
                 lty=1, lwd=1, col="red", lty.ci=2, lwd.ci=1, col.ci="red", 
                 mark.time=TRUE, col.surv="blue", lty.surv=2, lwd.surv=1,
                 ...)

Arguments

x
Output from msm, representing a fitted multi-state model object.
from
State from which to consider survival. Defaults to state 1.
to
Absorbing state to consider. Defaults to the highest-labelled absorbing state.
range
Vector of two elements, giving the range of times to plot for.
covariates
Covariate values for which to evaluate the expected probabilities. This can either be: the string "mean", denoting the means of the covariates in the data (this is the default), the number 0, indicating that all the cova
ci
If "none" (the default) no confidence intervals are plotted. If "normal" or "bootstrap", confidence intervals are plotted based on the respective method in pmatr
B
Number of bootstrap or normal replicates for the confidence interval. The default is 100 rather than the usual 1000, since these plots are for rough diagnostic purposes.
interp
If interp="start" (the default) then the entry time into the absorbing state is assumed to be the time it is first observed in the data. If interp="midpoint" then the entry time into the absorbing state is assumed
legend.pos
Vector of the $x$ and $y$ position, respectively, of the legend.
xlab
x axis label.
ylab
y axis label.
lty
Line type for the fitted curve. See par.
lwd
Line width for the fitted curve. See par.
col
Colour for the fitted curve. See par.
lty.ci
Line type for the fitted curve confidence limits. See par.
lwd.ci
Line width for the fitted curve confidence limits. See par.
col.ci
Colour for the fitted curve confidence limits. See par.
mark.time
Mark the empirical survival curve at each censoring point, see lines.survfit.
col.surv
Colour for the empirical survival curve, passed to lines.survfit. See par.
lty.surv
Line type for the empirical survival curve, passed to lines.survfit. See par.
lwd.surv
Line width for the empirical survival curve, passed to lines.survfit. See par.
...
Other arguments to be passed to the plot function which draws the fitted curve, or the lines.survfit function which draws the empirical cu

Details

If the data represent observations of the process at arbitrary times, then the first occurrence of the absorbing state in the data will usually be greater than the actual first transition time to that state. Therefore the Kaplan-Meier estimate of the survival probability will be an overestimate.

The method of Turnbull (1976) could be used to give a non-parametric estimate of the time to an interval-censored event, and compared to the equivalent estimate from a multi-state model. This is implemented in the CRAN package interval (Fay and Shaw 2010). This currently only handles time-homogeneous models.

References

Turnbull, B. W. (1976) The empirical distribution function with arbitrarily grouped, censored and truncated data. J. R. Statist. Soc. B 38, 290-295.

Fay, MP and Shaw, PA (2010). Exact and Asymptotic Weighted Logrank Tests for Interval Censored Data: The interval R package. Journal of Statistical Software. http://www.jstatsoft.org/v36/ i02/. 36 (2):1-34.

See Also

survfit, plot.survfit, plot.prevalence.msm