explore_plot {sMSROC}

Graphical exploratory data analysis

Description

Plots the kernel density estimations of the biomarker distributions on positive and negative individuals.

Usage

explore_plot(marker, status, observed.time, left, right, time)

Arguments

marker

vector with the biomarker values.

status

numeric response vector. The highest value is assumed to stand for the subjects having the event under study. The lowest value, for those who do not. Any other value will not be considered.

observed.time

vector with the observed times for each subject, for prognosis scenarios under right censorship. Notice that these values may be the event times or the censoring times.

left

vector containing the lower edges of the observed intervals. It is mandatory in prognosis scenarios under interval censorship and ignored in other situations.

right

vector with the upper edges of the observed intervals. It is mandatory in prognosis scenarios under interval censorship and ignored in other situations. The infinity is admissible as value (indicated as inf).

time

point of time at which the sMS ROC curve estimator will be computed. The default value is 1.

Value

The ouput is a list with three components:

plot

object of class ggplot.

neg

vector with the biomarker values on negative individuals.

pos

vector with the marker values on positive individuals.

See Also

explore_table

Examples

data(diabet)
explore_plot(marker=diabet$stab.glu, status=diabet$diab)