eha (version 2.4-5)

coxreg.fit: Cox regression

Description

Called by coxreg, but a user can call it directly.

Usage

coxreg.fit(X, Y, rs, weights, t.offset = NULL,
strats, offset, init, max.survs,
method = "breslow", center = TRUE,
boot = FALSE, efrac = 0, calc.hazards = TRUE,
calc.martres = TRUE, control, verbose = TRUE)

Arguments

X

The design matrix.

Y

The survival object.

rs

The risk set composition. If absent, calculated.

weights

Case weights; time-fixed or time-varying.

t.offset

Case offset; time-varying.

strats

The stratum variable. Can be absent.

offset

Offset. Can be absent.

init

Start values. If absent, equal to zero.

max.survs

Sampling of risk sets? If so, gives the maximum number of survivors in each risk set.

method

Either "efron" (default) or "breslow".

center

See coxreg.

boot

Number of bootstrap replicates. Defaults to FALSE, no bootstrapping.

efrac

Upper limit of fraction failures in 'mppl'.

calc.hazards

Should estimates of baseline hazards be calculated?

calc.martres

Should martingale residuals be calculated?

control

See coxreg

verbose

Should Warnings about convergence be printed?

Value

A list with components

coefficients

Estimated regression parameters.

var

Covariance matrix of estimated coefficients.

loglik

First component is value at init, second at maximum.

score

Score test statistic, at initial value.

linear.predictors

Linear predictors.

residuals

Martingale residuals.

hazard

Estimated baseline hazard. At value zero of 'design' variables.

means

Means of the columns of the design matrix.

bootstrap

The bootstrap replicates, if requested on input.

conver

TRUE if convergence.

f.conver

TRUE if variables converged.

fail

TRUE if failure.

iter

Number of performed iterations.

Details

rs is dangerous to use when NA's are present.

See Also

coxreg, risksets

Examples

 X <- as.matrix(data.frame(
                x=     c(0, 2,1,4,1,0,3),
                sex=   c(1, 0,0,0,1,1,1)))
 time <- c(1,2,3,4,5,6,7)
 status <- c(1,1,1,0,1,1,0)
 stratum <- rep(1, length(time))

 coxreg.fit(X, Surv(time, status), strats = stratum, max.survs = 6,
     control = list(eps=1.e-4, maxiter = 10, trace = FALSE))