getEPV function

getEPV

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

getEPV(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.

Returns

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

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.

Examples

data("X_proteomic")
data("Y_proteomic")
X <- X_proteomic
Y <- Y_proteomic
getEPV(X,Y)

Author(s)

Pedro Salguero Garcia. Maintainer: pedsalga@upv.edu.es