# plot.dynreg: Plots estimates and test-processes In timereg: Flexible Regression Models for Survival Data

## 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

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19``` ```## 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

Thomas Scheike

## References

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

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14``` ```### 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) ```

timereg documentation built on Oct. 13, 2021, 5:06 p.m.