Obtains the \(S_0(t)\) and \(\beta_{overall}\) parameters for recalibration

Calculates the recalibration type 2 parameters for the recalibrate_data and returns a list with the two needed parameters \(S_0(t)\), the survival estimation in the time \(t\) for the external validation data, and \(\beta_{overall}\), the importance that the \(\beta \cdot X\) values should have over the external validation data.

The survival function estimation is calculated as a Weibull distribution. A Weibull model is derived in the external validation cohort and the value estimated by the model for the time \(t\) is used as the recalibration of \(S_0(t)\). The importance of the \(\beta \cdot X\) is calculated by deriving a Cox model using as only covariate the model \(\beta \cdot X\) values. The derived Cox model coefficient is used as \(\beta_{overall}\).

Usage

get_recalibrate_params_type_2_cox(time, event, betax)

Arguments

time

time of follow up for each patient, must be numeric

event

if the patient has suffered an event during follow up, must be numeric \(1\) event \(0\) othercase

betax

the betax values, \(\beta X\), of the original predictions, must be numeric

Value

a list with two elements:

• S0: \(S_0(t)\)

• beta_overall: \(\beta_{overall}\) value from the type 2 recalibration

Examples

if (FALSE) { # \dontrun{
get_recalibrate_params_type_2_cox(data, betax, t)
} # }