coxModelFrame

coxModelFrame.coxph

coxModelFrame.cph

coxModelFrame.phreg

The fitted Cox regression model object either
obtained with <code>coxph</code> (survival package), <code>cph</code>
(rms package), or <code>phreg</code> (mets package).

object

[logical] Should the variables of the linear predictor be added ?

center

Extract the design matrix used to train a Cox model. Should contain the time of event, the type of event, 
the variable for the linear predictor, the strata variables and the date of entry (in case of delayed entry).

Implementation of the following methods for event history analysis.
Risk regression models for survival endpoints also in the presence of competing
risks are fitted using binomial regression based on a time sequence of binary
event status variables. A formula interface for the Fine-Gray regression model
and an interface for the combination of cause-specific Cox regression models.
A toolbox for assessing and comparing performance of risk predictions (risk
markers and risk prediction models). Prediction performance is measured by the
Brier score and the area under the ROC curve for binary possibly time-dependent
outcome. Inverse probability of censoring weighting and pseudo values are used
to deal with right censored data. Lists of risk markers and lists of risk models
are assessed simultaneously. Cross-validation repeatedly splits the data, trains
the risk prediction models on one part of each split and then summarizes and
compares the performance across splits.

coxModelFrame: Extract the design matrix used to train a Cox model

Description

Usage

Arguments