coxph.object {survival} | R Documentation |
Proportional Hazards Regression Object
Description
This class of objects is returned by the coxph
class of functions
to represent a fitted proportional hazards model.
Objects of this class have methods for the functions print
,
summary
, residuals
, predict
and survfit
.
COMPONENTS
The following components must be included in a legitimate coxph
object.
- coefficients
- the coefficients of the linear predictor, which multiply the columns of the
model matrix. If the model is over-determined there will be missing
values in the vector corresponding to the redundant columns in the model
matrix.
- var
- the variance matrix of the coefficients. Rows and columns corresponding to
any missing coefficients are set to zero.
- naive.var
- this component will be present only if the
robust
option was true. If so,
the var
component will contain the robust estimate of variance, and this
component will contain the ordinary estimate.
- loglik
- a vector of length 2 containing the log-likelihood with the initial values and
with the final values of the coefficients.
- score
- value of the efficient score test, at the initial value of the coefficients.
- rscore
- the robust log-rank statistic, if a robust variance was requested.
- wald.test
- the Wald test of whether the final coefficients differ from the initial values.
- iter
- number of iterations used.
- linear.predictors
- the vector of linear predictors, one per subject.
- residuals
- the martingale residuals.
- means
- vector of column means of the X matrix. Subsequent survival curves are
adjusted to this value.
- n
- the number of observations used in the fit.
- weights
- the vector of case weights, if one was used.
- method
- the computation method used.
- na.action
- the
na.action
attribute, if any, that was returned by the na.action
routine.
The object will also contain the following, for documentation see the lm
object: terms
, assign
, formula
, call
, and, optionally, x
, y
,
and/or frame
.
See Also
coxph
, coxph.detail
, cox.zph
, survfit
, residuals.coxph
, survreg