coxsurv.fit: A direct interface to the 'computational engine' of...

In survival: Survival Analysis

A direct interface to the ‘computational engine’ of survfit.coxph

Description

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.

Usage

coxsurv.fit(ctype, stype, se.fit, varmat, cluster, 
            y, x, wt, risk, position, strata, oldid,
            y2, x2, risk2, strata2, id2, unlist=TRUE)

Arguments

stype	survival curve computation: 1=direct, 2=exp(-cumulative hazard)
ctype	cumulative hazard computation: 1=Breslow, 2=Efron
se.fit	if TRUE, compute standard errors
varmat	the variance matrix of the coefficients
cluster	vector to control robust variance
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.
risk	the risk score exp(X beta + offset) from the fitted Cox model.
position	optional argument controlling what is counted as 'censored'. Due to time dependent covariates, for instance, a subject might have start, stop times of (1,5)(5,30)(30,100). Times 5 and 30 are not 'real' censorings. Position is 1 for a real start, 2 for an actual end, 3 for both, 0 for neither.
strata	strata variable used in the Cox model. This will be a factor.
oldid	identifier for subjects with multiple rows in the original data.
y2, x2, risk2, strata2	variables for the hypothetical subjects, for which prediction is desired
id2	optional; if present and not NULL this should be a vector of identifiers of length nrow(x2). A non-null value signifies that x2 contains time dependent covariates, in which case this identifies which rows of x2 go with each subject.
unlist	if FALSE the result will be a list with one element for each strata. Otherwise the strata are “unpacked” into the form found in a survfit object.

Value

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.

Note

The source code for for both this function and survfit.coxph is written using noweb. For complete documentation see the inst/sourcecode.pdf file.

Author(s)

Terry Therneau

See Also

survfit.coxph

survival documentation built on June 22, 2024, 10:49 a.m.