R: Plot method for a probtrans object

plot.probtrans {mstate} | R Documentation

## Plot method for a probtrans object

### Description

Plot method for an object of class 'probtrans'. It plots the transition probabilities as estimated by `probtrans`.

### Usage

    ## S3 method for class 'probtrans'
    plot(
      x,
      from = 1,
      type = c("filled", "single", "separate", "stacked"),
      ord,
      cols,
      xlab = "Time",
      ylab = "Probability",
      xlim,
      ylim,
      lwd,
      lty,
      cex,
      legend,
      legend.pos = "right",
      bty = "n",
      xaxs = "i",
      yaxs = "i",
      use.ggplot = FALSE,
      conf.int = 0.95,
      conf.type = c("log", "plain", "none"),
      label,
      ...
    )

### Arguments

`x` | Object of class 'probtrans', containing estimated transition probabilities
`from` | The starting state from which the probabilities are used to plot
`type` | One of `"stacked"` (default), `"filled"`, `"single"` or `"separate"`; in case of `"stacked"`, the transition probabilities are stacked and the distance between two adjacent curves indicates the probability, this is also true for `"filled"`, but the space between adjacent curves are filled, in case of `"single"`, the probabilities are shown as different curves in a single plot, in case of `"separate"`, separate plots are shown for the estimated transition probabilities
`ord` | A vector of length equal to the number of states, specifying the order of plotting in case type=`"stacked"` or `"filled"`
`cols` | A vector specifying colors for the different transitions; default is a palette from green to red, when type=`"filled"` (reordered according to `ord`, and 1 (black), otherwise
`xlab` | A title for the x-axis; default is `"Time"`
`ylab` | A title for the y-axis; default is `"Probability"`
`xlim` | The x limits of the plot(s), default is range of time
`ylim` | The y limits of the plot(s); if ylim is specified for type="separate", then all plots use the same ylim for y limits
`lwd` | The line width, see `par`; default is 1
`lty` | The line type, see `par`; default is 1
`cex` | Character size, used in text; only used when type=`"stacked"` or `"filled"`
`legend` | Character vector of length equal to the number of transitions, to be used in a legend; if missing, numbers will be used; this and the legend arguments following are ignored when type="separate"
`legend.pos` | The position of the legend, see `legend`; default is `"topleft"`
`bty` | The box type of the legend, see `legend`
`xaxs` | See `par`, default is "i", for type=`"stacked"`
`yaxs` | See `par`, default is "i", for type=`"stacked"`
`use.ggplot` | Default FALSE, set TRUE for ggplot version of plot
`conf.int` | Confidence level (%) from 0-1 for probabilities, default is 0.95 (95% CI). Setting to 0 removes the CIs.
`conf.type` | Type of confidence interval - either "log" or "plain" . See function details for details.
`label` | Only relevant for type = "filled" or "stacked", set to "annotate" to have state labels on plot, or leave unspecified.
`...` | Further arguments to plot

### Details

Regarding confidence intervals: let p denote a predicted probability, σ its estimated standard error, and z_{α/2} denote the critical value of the standard normal distribution at confidence level 1 - α.

The confidence interval of type "plain" is then

p \pm z_{α/2} * σ

The confidence interval of type "log", based on the Delta method, is then

\exp(\log(p) \pm z_{α/2} * σ / p)

### Value

No return value

### Author(s)

Hein Putter H.Putter@lumc.nl

Edouard F. Bonneville e.f.bonneville@lumc.nl

### See Also

`probtrans`

### Examples

    # transition matrix for illness-death model
    tmat <- trans.illdeath()
    # data in wide format, for transition 1 this is dataset E1 of
    # Therneau and Grambsch (2000)
    tg <- data.frame(illt=c(1,1,6,6,8,9),ills=c(1,0,1,1,0,1),
            dt=c(5,1,9,7,8,12),ds=c(1,1,1,1,1,1),
            x1=c(1,1,1,0,0,0),x2=c(6:1))
    # data in long format using msprep
    tglong <- msprep(time=c(NA,"illt","dt"),status=c(NA,"ills","ds"),
    		data=tg,keep=c("x1","x2"),trans=tmat)
    # events
    events(tglong)
    table(tglong$status,tglong$to,tglong$from)
    # expanded covariates
    tglong <- expand.covs(tglong,c("x1","x2"))
    # Cox model with different covariate
    cx <- coxph(Surv(Tstart,Tstop,status)~x1.1+x2.2+strata(trans),
    	data=tglong,method="breslow")
    summary(cx)
    # new data, to check whether results are the same for transition 1 as
    # those in appendix E.1 of Therneau and Grambsch (2000)
    newdata <- data.frame(trans=1:3,x1.1=c(0,0,0),x2.2=c(0,1,0),strata=1:3)
    msf <- msfit(cx,newdata,trans=tmat)
    # probtrans
    pt <- probtrans(msf,predt=0)
    # default plot
    plot(pt,ord=c(2,3,1),lwd=2,cex=0.75)
    # filled plot
    plot(pt,type="filled",ord=c(2,3,1),lwd=2,cex=0.75)
    # single plot
    plot(pt,type="single",lwd=2,col=rep(1,3),lty=1:3,legend.pos=c(8,1))
    # separate plots
    par(mfrow=c(2,2))
    plot(pt,type="sep",lwd=2)
    par(mfrow=c(1,1))

    # ggplot version - see vignette for details
    library(ggplot2)
    plot(pt, ord=c(2,3,1), use.ggplot = TRUE)

[Package mstate version 0.3.1 Index]