plot.thregIcure: plot survival, hazard and density curves
In thregI: Threshold Regression for Interval-Censored Data with a Cure Rate Option

Display the graphs of the estimated survival, hazard or density function at different levels of a categorical variable which has been included in the threshold regression cure-rate model by thregIcure(). There are three options, "sv", "hz" and "ds" are for survival, hazard and density function, respectively.

1
2
3

## S3 method for class 'thregIcure'
plot(x,var,scenario,graph,nolegend=0,nocolor=0,...)

`x`	a thregIcure object.
`var`	specifies the name of the variable which is required to be categorical. The use of the var argument is the same as that in the plot.thregI().
`scenario`	specifies a scenario for predicted plots.
`graph`	specifies the type of curves to be generated. The "hz" option is to plot hazard function accommodated a cure rate, the "sv" option is to plot survival function accommodated a cure rate and the "ds" option is to plot density function accommodated a cure rate.
`nolegend`	The use of the nolegend argument is the same as that in the plot.thregI().
`nocolor`	The use of the nolegend argument is the same as that in the plot.thregI().
`...`	for future methods

#load the data "hdsd"
data("hdsd", package="thregI")

#transform categorical variable Noadyn into factor variable f.noadyn
hdsd$f.noadyn=factor(hdsd$Noadyn)

#fit the threshold regression cure-rate model
#the covariates are TR360, Noadyn, Sex and Age
fit<-thregIcure(Surv(left, right, type='interval2')~f.noadyn|TR360|Sex+Age, data=hdsd)

#plot estimated hazard, survival and density function
#subject is ambulatory (Noadyn1=1), TR360 = 1.5, male and 30 years old
plot.thregIcure(fit, var=f.noadyn, scenario=TR360(1.5)+Sex(1)+Age(30), graph = "sv", nocolor = 1)
plot.thregIcure(fit, var=f.noadyn, scenario=TR360(1.5)+Sex(1)+Age(30), graph = "hz", nocolor = 1)
plot.thregIcure(fit, var=f.noadyn, scenario=TR360(1.5)+Sex(1)+Age(30), graph = "ds", nocolor = 1)