R: Plots estimates and test-processes

plot.dynreg {timereg} | R Documentation

## Plots estimates and test-processes

### Description

This function plots the non-parametric cumulative estimates for the additive risk model or the test-processes for the hypothesis of constant effects with re-sampled processes under the null.

### Usage

    ## S3 method for class 'dynreg'
    plot(x, type = "eff.smooth", pointwise.ci = 1,
      hw.ci = 0, sim.ci = 0, robust = 0, specific.comps = FALSE,
      level = 0.05, start.time = 0, stop.time = 0, add.to.plot = FALSE,
      mains = TRUE, xlab = "Time", ylab = "Cumulative coefficients",
      score = FALSE, ...)

### Arguments

`x` | the output from the "dynreg" function.
`type` | the estimator plotted. Choices "eff.smooth", "ms.mpp", "0.mpp" and "ly.mpp". See the dynreg function for more on this.
`pointwise.ci` | if >1 pointwise confidence intervals are plotted with lty=pointwise.ci
`hw.ci` | if >1 Hall-Wellner confidence bands are plotted with lty=hw.ci. Only 0.95 % bands can be constructed.
`sim.ci` | if >1 simulation based confidence bands are plotted with lty=sim.ci. These confidence bands are robust to non-martingale behaviour.
`robust` | robust standard errors are used to estimate standard error of estimate, otherwise martingale based estimate are used.
`specific.comps` | all components of the model is plotted by default, but a list of components may be specified, for example first and third "c(1,3)".
`level` | gives the significance level.
`start.time` | start of observation period where estimates are plotted.
`stop.time` | end of period where estimates are plotted. Estimates thus plotted from [start.time, max.time].
`add.to.plot` | to add to an already existing plot.
`mains` | add names of covariates as titles to plots.
`xlab` | label for x-axis.
`ylab` | label for y-axis.
`score` | to plot test processes for test of time-varying effects along with 50 random realization under the null-hypothesis.
`...` | unused arguments - for S3 compatibility

### Author(s)

Thomas Scheike

### References

Martinussen and Scheike, Dynamic Regression Models for Survival Data, Springer (2006).

### Examples

    ### runs slowly and therefore donttest
    data(csl)
    indi.m<-rep(1,length(csl$lt))

    # Fits time-varying regression model
    out<-dynreg(prot~treat+prot.prev+sex+age,csl,
    Surv(lt,rt,indi.m)~+1,start.time=0,max.time=3,id=csl$id,
    n.sim=100,bandwidth=0.7,meansub=0)

    par(mfrow=c(2,3))
    # plots estimates
    plot(out)
    # plots tests-processes for time-varying effects
    plot(out,score=TRUE)

[Package timereg version 1.9.4 Index]