plot.flexsurvreg: Plots of fitted flexible survival models
In flexsurv: Flexible parametric survival models

Description Usage Arguments Note Author(s) See Also

Plot fitted survival, cumulative hazard or hazard from a parametric model against nonparametric estimates to diagnose goodness-of-fit.

## S3 method for class 'flexsurvreg'
plot(x, X=NULL, type="survival", t=NULL, start=NULL,
        est=TRUE, ci=NULL, B=1000, cl=0.95,
        col.obs="black", lty.obs=1, lwd.obs=1,
        col="red", lty=1, lwd=2,
        col.ci=NULL, lty.ci=2, lwd.ci=1,
        add=FALSE,...)

`x`	Output from `flexsurvreg` or `flexsurvspline`, representing a fitted survival model object.
`X`	Matrix of covariate values to produce fitted survival curves for. Columns represent different covariates, and rows represent multiple curves. For example `matrix(c(1,2),nrow=2)` if there is only one covariate in the model, and we want to plot curves for covariate values of 1 and 2. For “factor” (categorical) covariates, the values of the contrasts representing factor levels (as returned by the `contrasts` function) should be used. For example, for a covariate `agegroup` specified as an unordered factor with levels `20-29, 30-39, 40-49, 50-59`, and baseline level `20-29`, there are three contrasts. To plot curves for groups `20-29` and `40-49`, supply `X = rbind(c(0,0,0), c(0,1,0))`, since all contrasts are zero for the baseline level, and the second contrast is “turned on” for the third level `40-49`. If there are only factor covariates in the model, then Kaplan-Meier 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.
`type`	`"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.
`t`	Vector of times to plot fitted values for, see `summary.flexsurvreg`.
`start`	Left-truncation points, see `summary.flexsurvreg`.
`est`	Plot fitted curves (`TRUE` or `FALSE`.)
`ci`	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.
`B`	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.
`cl`	Width of confidence intervals, by default 0.95 for 95% intervals.
`col.obs`	Colour of the nonparametric curve.
`lty.obs`	Line type of the nonparametric curve.
`lwd.obs`	Line width of the nonparametric curve.
`col`	Colour of the fitted parametric curve(s).
`lty`	Line type of the fitted parametric curve(s).
`lwd`	Line width of the fitted parametric curve(s).
`col.ci`	Colour of the fitted confidence limits, defaulting to the same as for the fitted curve.
`lty.ci`	Line type of the fitted confidence limits.
`lwd.ci`	Line width of the fitted confidence limits.
`add`	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.

C. H. Jackson chris.jackson@mrc-bsu.cam.ac.uk

flexsurvreg

flexsurv documentation built on May 2, 2019, 6:23 p.m.