Coxmos (version 1.1.2)

plot_divergent.biplot: plot_divergent.biplot

Description

Generates a divergent biplot visualizing the distribution of a qualitative variable against a quantitative variable, further categorized by an event matrix.

Usage

plot_divergent.biplot(
  X,
  Y,
  NAMEVAR1,
  NAMEVAR2,
  BREAKTIME,
  x.text = "N. of Samples"
)

Value

A 'ggplot2' two side bar plot. X axis represent the number of samples per each NAMEVAR1 factor levels and Y axis, the X NAMEVAR2 numerical variables categorize in groups of breaks.

Arguments

X

Numeric matrix or data.frame. Explanatory variables with "NAMEVAR1" and "NAMEVAR2" variables. "NAMEVAR1" must be a factor variable.

Y

Numeric matrix or data.frame. Response variables. Object must have two columns named as "time" and "event". For event column, accepted values are: 0/1 or FALSE/TRUE for censored and event observations.

NAMEVAR1

Character. Factor variable name (must be located in colnames(X) and have to have two levels).

NAMEVAR2

Character. Numerical variable name (must be located in colnames(X)).

BREAKTIME

Numeric. Size of time to split the data into "total_time / BREAKTIME + 1" points. If BREAKTIME = NULL, "n.breaks" is used (default: NULL).

x.text

Character. Title for X axis.

Author

Pedro Salguero Garcia. Maintainer: [e-mail]

Details

The function plot_divergent.biplot is designed to offer a comprehensive visualization of the relationship between a qualitative and a quantitative variable, while also taking into account an associated event matrix. The qualitative variable, denoted by "NAMEVAR1", is expected to be a factor with two levels, and the quantitative variable, "NAMEVAR2", is numerically represented. The event matrix, "Y", consists of two columns: "time" and "event". The "event" column indicates whether an observation is censored or an event, represented by binary values (0/1 or FALSE/TRUE).

The function processes the input data to categorize the quantitative variable into groups based on the specified "BREAKTIME" parameter. Each group represents a range of values for the quantitative variable. The resulting plot displays the number of samples for each level of the qualitative variable on the X-axis, while the Y-axis represents the categorized groups of the quantitative variable. The bars in the plot are further colored based on the event type, providing a clear distinction between censored and event observations.

Examples

X <- data.frame(sex = factor(c("M","M","F","F","F","M","F","M","M")),
age = as.numeric(c(22,23,25,28,32,30,29,33,32)))

Y = data.frame(time = c(24,25,28,29,22,26,22,23,24),
event = c(TRUE,TRUE,FALSE,TRUE,FALSE,TRUE,TRUE,FALSE,FALSE))

NAMEVAR1 = "sex"
NAMEVAR2 = "age"
plot_divergent.biplot(X, Y, NAMEVAR1, NAMEVAR2, BREAKTIME = 5, x.text = "N. of Patients")