pmpec  R Documentation 
Calculation of prediction error curve from a survival response and predicted probabilities of survival.
pmpec(object, response=NULL, x=NULL, times, model.args=NULL,
type=c("PErr","NoInf"), external.time=NULL, external.status=NULL,
data=NULL)
object 
fitted model of a class for which the interface function 
response 
Either a survival object (with 
x 

times 
vector of time points at which the prediction error is to be estimated. 
model.args 
named list of additional arguments, e.g. complexity value, which are to be passed to 
type 
type of output: Estimated prediction error (default) or no information error (prediction error obtained by permuting the data). 
external.time 
optional vector of time points, used for censoring distribution. 
external.status 
optional vector of status values, used for censoring distribution. 
data 
Data frame containing 
Prediction error of survival data is measured by the Brier score, which considers the squared difference of the true event status at a given time point and the predicted event status by a risk prediction model at that time. A prediction error curve is the weighted mean Brier score as a function of time at time points in times
(see References).
pmpec
requires a predictProb
method for the class of the fitted model, i.e. for a model of class class
predictProb.class
.
pmpec
is implemented to behave similar to function pec
of package pec, which provides several predictProb
methods.
In bootstrap framework, data
contains only a part of the full data set. For censoring distribution, the full data should be used to avoid extreme variance in case of small data sets. For that, the observed times and status values can be passed as argument external.time
and external.status
.
Vector of prediction error estimates at each time point given in time
.
Harald Binder
Gerds, A. and Schumacher, M. (2006) Consistent estimation of the expected Brier score in general survival models with rightcensored event times. Biometrical Journal, 48, 1029–1040.
Schoop, R. (2008) Predictive accuracy of failure time models with longitudinal covariates. PhD thesis, University of Freiburg. http://www.freidok.unifreiburg.de/volltexte/4995/.
predictProb
, pec
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