Determine the Brier score for a fitted model

Evaluate the Brier score, i.e. prediction error, for a fitted model on new data. To be used as argument aggregation.fun in peperr call.

aggregation.brier(full.data=NULL, response, x, model, cplx=NULL,  
type=c("apparent", "noinf"), fullsample.attr = NULL, ...)

Arguments

full.data	passed from peperr, but not used for calculation of the Brier score.
response	vector of binary response.
x	n*p matrix of covariates.
model	model fitted as returned by a fit.fun, as used in a call to peperr.
cplx	passed from peperr, but not necessary for calculation of the Brier score.
type	character.
fullsample.attr	passed from peperr, but not necessary for calculation of the Brier score.
...	additional arguments, passed to predict function.

Details

The empirical Brier score is the mean of the squared difference of the risk prediction and the true value of all observations and takes values between 0 and 1, where small values indicate good prediction performance of the risk prediction model.

Value

Scalar, indicating the empirical Brier score.