plot.squant {squant}

Plot SQUANT result

Description

plot plots the subgroup identification performance.

Usage

## S3 method for class 'squant'
plot(x, trt.name = "Trt", ctrl.name = "Ctrl", ...)

Arguments

x

A squant object. The output of squant function.

trt.name

The name used on plot for the treatment arm.

ctrl.name

The name used on plot for the control arm.

...

Ignored.

Details

An interaction plot is plotted for the predictive case and a group plot is plotted for the prognostic case.

Value

A ggplot.

Examples

#toy example#
set.seed(888)
x=as.data.frame(matrix(rnorm(200),100,2))
names(x) = c("x1", "x2")
trt = sample(0:1, size=100, replace=TRUE)
y= 2*x[,2]*trt+rnorm(100)
data = cbind(y=y, trt=trt, x)
res = squant(yvar="y", censorvar=NULL, xvars=c("x1", "x2"),
             trtvar="trt", trtcd=1, data=data, type="c", weight=NULL,
             dir="larger", quant=NULL, xvars.keep=NULL, alpha=1,
             fold=2, n.cv = 10, FDR = 0.1, progress=FALSE)



#predictive case with continuous response#
set.seed(888)
x=as.data.frame(matrix(rnorm(20000),200,100))
names(x) = paste("x", 1:100,sep="")
trt = sample(0:1, size=200, replace=TRUE)
y=x[,1]+x[,2]*trt+rnorm(200)
data = cbind(y=y, trt=trt, x)
res = squant(yvar="y", censorvar=NULL, xvars=paste("x", 1:100,sep=""),
             trtvar="trt", trtcd=1, data=data, type="c", weight=NULL,
             dir="larger", quant=NULL, xvars.keep=NULL, alpha=1,
             fold=5, n.cv = 50, FDR = 0.1)
res
#fitted signature#
res$squant.fit
#performance of the identified subgroup#
#including:
#  interaction p value,
#  p valve of trt difference in positive group,
#  p value of trt difference in negative group,
#  and stats for each arm in each group.
res$performance
#interpretation#
res$interpretation1
res$interpretation2

#evaluation of prediction performance#
eval.res = eval_squant(yvar="y", censorvar=NULL, trtvar="trt", trtcd=1, dir="larger",
                       type="c", data=data, squant.out=res, brief=FALSE)
#plot the subgroups#
plot(res, trt.name="Trt", ctrl.name="Ctrl")
plot(eval.res, trt.name="Trt", ctrl.name="Ctrl")



#prognostic case with survival response#
set.seed(888)
x=as.data.frame(matrix(rnorm(20000),200,100))
names(x) = paste("x", 1:100,sep="")
y=10*(10+x[,1]+rnorm(200))
data = cbind(y=y, x)
data$event = sample(c(rep(1,150),rep(0,50)))
res = squant(yvar="y", censorvar="event", xvars=paste("x", 1:100,sep=""),
             trtvar=NULL, trtcd=NULL, data=data, type="s", weight=NULL,
             dir="larger", quant=NULL, xvars.keep=NULL, alpha=1,
             fold=5, n.cv = 50, FDR = 0.1)
res

#fitted signature#
res$squant.fit
#performance of the identified subgroup#
res$performance
#evaluation of prediction performance#
eval.res = eval_squant(yvar="y", censorvar="event", trtvar=NULL, trtcd=NULL, dir="larger",
                       type="s", data=data, squant.out=res, brief=FALSE)

#plot the subgroups#
plot(res, trt.name=NULL, ctrl.name=NULL)
plot(eval.res, trt.name=NULL, ctrl.name=NULL)