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.

Usage

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.