explore_table {sMSROC}

Exploratory data analysis

Description

This function provides descriptive statistics for the pooled sample and the samples of positive, negative individuals and those whose condition is unknown.

Usage

explore_table(marker, status, observed.time, left, right, time, d, ...)

Arguments

marker

vector with the biomarker values. It is a mandatory parameter.

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.

d

number of decimal figures to which the results will be rounded.

...

additional parameters of the flextable function which allow to customize the output table.

Details

The function computes the following descriptive statistics for the pooled sample and the samples of the different groups of individuals: minimum, maximun, mean, variance, standard deviation, and first, second and third quartiles.

Value

The ouput is a list with two components:

summary

matrix whose columns are the statistics described above and the rows show the corresponding results for each sample.

table

object of class flextable that represent the matrix in summary in a customizable table.

See Also

explore_plot

Examples

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