CoxModel  R Documentation 
Fits a Cox proportional hazards regression model. Time dependent variables, time dependent strata, multiple events per subject, and other extensions are incorporated using the counting process formulation of Andersen and Gill.
CoxModel(ties = c("efron", "breslow", "exact"), ...) CoxStepAICModel( ties = c("efron", "breslow", "exact"), ..., direction = c("both", "backward", "forward"), scope = list(), k = 2, trace = FALSE, steps = 1000 )
ties 
character string specifying the method for tie handling. 
... 
arguments passed to 
direction 
mode of stepwise search, can be one of 
scope 
defines the range of models examined in the stepwise search.
This should be a list containing components 
k 
multiple of the number of degrees of freedom used for the penalty.
Only 
trace 
if positive, information is printed during the running of

steps 
maximum number of steps to be considered. 
Surv
Default values and further model details can be found in the source links below.
In calls to varimp
for CoxModel
and
CoxStepAICModel
, numeric argument base
may be specified for the
(negative) logarithmic transformation of pvalues [defaul: exp(1)
].
Transformed pvalues are automatically scaled in the calculation of variable
importance to range from 0 to 100. To obtain unscaled importance values, set
scale = FALSE
.
MLModel
class object.
coxph
,
coxph.control
, stepAIC
,
fit
, resample
library(survival) fit(Surv(time, status) ~ ., data = veteran, model = CoxModel)
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