R: A direct interface to the 'computational engine' of...

survfitcoxph.fit {survival}

R Documentation

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

survfitcoxph.fit(y, x, wt, x2, risk, newrisk, strata, se.fit, survtype,
vartype, varmat, id, y2, strata2, unlist=TRUE)

Arguments

`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 `x`.
`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 `TRUE` the standard errors of the curve(s) are returned
`survtype`	1=Kalbfleish-Prentice, 2=Nelson-Aalen, 3=Efron. It is usual to match this to the approximation for ties used in the `coxph` model: KP for ‘exact’, N-A for ‘breslow’ and Efron for ‘efron’.
`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 `nrow(x2)`. A mon-null value signifies that `x2` contains time dependent covariates, in which case this identifies which rows of `x2` go with each subject.
`y2`	survival times, for time dependent prediction. It gives the time range (time1,time2] for each row of `x2`. Note: this must be a Surv object and thus contains a status indicator, which is never used in the routine, however.
`strata2`	vector of strata indicators for `x2`. This must be a factor.
`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