CoxModel {MachineShop} | 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 = NULL, 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 for the NULL
arguments and further model details can be
found in the source link below.
In calls to varimp
for CoxModel
and
CoxStepAICModel
, numeric argument base
may be specified for the
(negative) logarithmic transformation of p-values [defaul: exp(1)
].
Transformed p-values are automatically scaled in the calculation of variable
importance to range from 0 to 100. To obtain unscaled importance values, set
scale = FALSE
.
#' @return MLModel
class object.
coxph
,
coxph.control
, stepAIC
,
fit
, resample
library(survival) fit(Surv(time, status) ~ ., data = veteran, model = CoxModel)