coxsurv.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

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

survfit.coxph