getEPV.mb {Coxmos}

getEPV.mb

Description

Provides a quantitative assessment of the dataset by computing the Events per Variable (EPV) metric for multi-block data, which gauges the proportionality between observed events and the number of explanatory variables.

Usage

getEPV.mb(X, Y)

Arguments

X

Numeric matrix or data.frame. Explanatory variables. Qualitative variables must be transform into binary variables.

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.

Details

In the realm of survival analysis, the balance between observed events and explanatory variables is paramount. The getEPV function serves as a tool for researchers to ascertain this balance, which can be pivotal in determining the robustness and interpretability of subsequent statistical models. By evaluating the ratio of events in the Y matrix to the variables in the X matrix, the function yields the EPV metric. It is of utmost importance that the Y matrix encompasses two distinct columns, namely "time" and "event". The latter, "event", should strictly encapsulate binary values, delineating censored (either 0 or FALSE) and event (either 1 or TRUE) observations. To ensure the integrity of the data and the precision of the computation, the function is equipped with an error mechanism that activates if the "event" column remains undetected.

Value

Return the EPV value for a specific X (explanatory variables) and Y (time and censored variables) data.

Author(s)

Pedro Salguero Garcia. Maintainer: [e-mail]

Examples

data("X_multiomic")
data("Y_multiomic")
X <- X_multiomic
Y <- Y_multiomic
getEPV.mb(X,Y)