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Plot fitted survival, cumulative hazard or hazard from a parametric model against nonparametric estimates to diagnose goodness-of-fit. Alternatively plot a user-defined function of the model parameters against time.


# S3 method for flexsurvreg
  newdata = NULL,
  X = NULL,
  type = "survival",
  fn = NULL,
  t = NULL,
  start = 0,
  est = TRUE,
  ci = NULL,
  B = 1000,
  cl = 0.95,
  col.obs = "black",
  lty.obs = 1,
  lwd.obs = 1,
  col = "red",
  lty = 1,
  lwd = 2, = NULL, = 2, = 1,
  ylim = NULL,
  add = FALSE,



Output from flexsurvreg or flexsurvspline, representing a fitted survival model object.


Data frame containing covariate values to produce fitted values for. See summary.flexsurvreg.

If there are only factor covariates in the model, then Kaplan-Meier (or nonparametric hazard...) curves are plotted for all distinct groups, and by default, fitted curves are also plotted for these groups. To plot Kaplan-Meier and fitted curves for only a subset of groups, use plot(survfit()) followed by lines.flexsurvreg().

If there are any continuous covariates, then a single population Kaplan-Meier curve is drawn. By default, a single fitted curve is drawn with the covariates set to their mean values in the data - for categorical covariates, the means of the 0/1 indicator variables are taken.


Alternative way to supply covariate values, as a model matrix. See summary.flexsurvreg. newdata is an easier way.


"survival" for survival, to be plotted against Kaplan-Meier estimates from plot.survfit.

"cumhaz" for cumulative hazard, plotted against transformed Kaplan-Meier estimates from plot.survfit.

"hazard" for hazard, to be plotted against smooth nonparametric estimates from muhaz. The nonparametric estimates tend to be unstable, and these plots are intended just to roughly indicate the shape of the hazards through time. The min.time and max.time options to muhaz may sometimes need to be passed as arguments to plot.flexsurvreg to avoid an error here.

Ignored if "fn" is specified.


Custom function of the parameters to summarise against time. The first two arguments of the function must be t representing time, and start representing left-truncation points, and any remaining arguments must be parameters of the distribution. It should return a vector of the same length as t.


Vector of times to plot fitted values for, see summary.flexsurvreg.


Left-truncation points, see summary.flexsurvreg.


Plot fitted curves (TRUE or FALSE.)


Plot confidence intervals for fitted curves. By default, this is TRUE if one observed/fitted curve is plotted, and FALSE if multiple curves are plotted.


Number of simulations controlling accuracy of confidence intervals, as used in summary. Decrease for greater speed at the expense of accuracy, or set B=0 to turn off calculation of CIs.


Width of confidence intervals, by default 0.95 for 95% intervals.


Colour of the nonparametric curve.


Line type of the nonparametric curve.


Line width of the nonparametric curve.


Colour of the fitted parametric curve(s).


Line type of the fitted parametric curve(s).


Line width of the fitted parametric curve(s).

Colour of the fitted confidence limits, defaulting to the same as for the fitted curve.

Line type of the fitted confidence limits.

Line width of the fitted confidence limits.


y-axis limits: vector of two elements.


If TRUE, add lines to an existing plot, otherwise new axes are drawn.


Other options to be passed to plot.survfit or muhaz, for example, to control the smoothness of the nonparametric hazard estimates. The min.time and max.time options to muhaz may sometimes need to be changed from the defaults.


Some standard plot arguments such as "xlim","xlab" may not work. This function was designed as a quick check of model fit. Users wanting publication-quality graphs are advised to set up an empty plot with the desired axes first (e.g. with plot(...,type="n",...)), then use suitable lines functions to add lines.

If case weights were used to fit the model, these are used when producing nonparametric estimates of survival and cumulative hazard, but not for the hazard estimates.

See also


C. H. Jackson