vdplot: Plot variable dependence using an oblique random survival...

Description Usage Arguments Value Examples

View source: R/variable_dependence_plot.R

Description

Plot variable dependence using an oblique random survival forest

Usage

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vdplot(object, xvar, include.hist = TRUE, include.points = FALSE,
  ptsize = 0.75, ytype = "nonevent", event_lab = "death",
  nonevent_lab = "survival", fvar = NULL, flab = NULL,
  time_units = "years", xlab = xvar, xvar_units = NULL,
  xlvls = NULL, sub_times = NULL, se.show = FALSE)

Arguments

object

an ORSF object (i.e. object returned from the ORSF function)

xvar

a string giving the name of the x-axis variable

include.hist

if true, a histogram showing the distribution of values for the x-axis variable will be included at the bottom of the plot.

include.points

if true, the predictions for each observation are plotted along with a smoothed population estimate. Note that points are always included if xvar is categorical.

ptsize

only relevant if include.points = TRUE. The size of the points in the plot are determined by this numeric value.

ytype

String. Use 'event' if you would like to plot the probability of the event, and 'nonevent' if you prefer to plot the probability of a non-event.

event_lab

string that describes the event

nonevent_lab

string that describes a non-event.

fvar

(optional) a string indicating a variable to facet the plot with

flab

the labels to be printed describing the facet variable. For a facet variable with k categories, flab should be a vector with k labels, given in the same order as the levels of the facet variable.

time_units

the unit of time, e.g. days, since baseline.

xlab

the label to be printed describing the x-axis variable

xvar_units

the unit of measurement for the x-axis variable. For example, age is usually measured in years.

xlvls

a character vector giving the labels that correspond to categorical xvar. This does not need to be specified if xvar is continuous.

sub_times

the times you would like to plot predicted values for. If left unspecified, the ORSF function will use all of the times in oob_times.

se.show

if true, standard errors of the population estimate will be included in the plot.

Value

A ggplot2 object

Examples

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## Not run: 
data("pbc",package='survival')
pbc$status[pbc$status>=1]=pbc$status[pbc$status>=1]-1
pbc$time=pbc$time/365.25
pbc$id=NULL
fctrs<-c('trt','ascites','spiders','edema','hepato','stage')
for(f in fctrs)pbc[[f]]=as.factor(pbc[[f]])
pbc=na.omit(pbc)

orsf=ORSF(data=pbc, eval_time=5, ntree=30)

vdplot(object=orsf, xvar='bili', xlab='Bilirubin', xvar_units='mg/dl')

## End(Not run)

obliqueRSF documentation built on March 14, 2019, 1:06 a.m.