This program is mainly supplied to allow other packages to invoke the survfit.coxph function at a ‘data’ level rather than a ‘user’ level. It does no checks on the input data that is provided, which can lead to unexpected errors if that data is wrong.
1 2  survfitcoxph.fit(y, x, wt, x2, risk, newrisk, strata, se.fit, survtype,
vartype, varmat, id, y2, strata2, unlist=TRUE)

y 
the response variable used in the Cox model. (Missing values removed of course.) 
x 
covariate matrix used in the Cox model 
wt 
weight vector for the Cox model. If the model was unweighted use a vector of 1s. 
x2 
matrix describing the hypothetical subjects for which a
curve is desired. Must have the same number of columns as 
risk 
the risk score exp(X beta) from the fitted Cox model. If the model had an offset, include it in the argument to exp. 
newrisk 
risk scores for the hypothetical subjects 
strata 
strata variable used in the Cox model. This will be a factor. 
se.fit 
if 
survtype 
1=KalbfleishPrentice, 2=NelsonAalen, 3=Efron. It is
usual to match this to the approximation for ties used in the

vartype 
1=Greenwood, 2=Aalen, 3=Efron 
varmat 
the variance matrix of the coefficients 
id 
optional; if present and not NULL this should be
a vector of identifiers of length 
y2 
survival times, for time dependent prediction. It gives
the time range (time1,time2] for each row of 
strata2 
vector of strata indicators for 
unlist 
if 
a list containing nearly all the components of a survfit
object. All that is missing is to add the confidence intervals, the
type of the original model's response (as in a coxph object), and the
class.
The source code for for both this function and
survfit.coxph
is written using noweb. For complete
documentation see the inst/sourcecode.pdf
file.
Terry Therneau
survfit.coxph
Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.
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