explore_plot: Graphical exploratory data analysis

In sMSROC: Assessment of Diagnostic and Prognostic Markers

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)

sMSROC documentation built on May 29, 2024, 1:43 a.m.