coxreg.fit: Cox regression
In eha: Event History Analysis

coxreg.fit

R Documentation

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 = "efron",
  boot = FALSE,
  efrac = 0,
  calc.martres = TRUE,
  control,
  verbose = TRUE,
  calc.hazards = NULL,
  center = NULL
)

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".
`boot`	Number of bootstrap replicates. Defaults to FALSE, no bootstrapping.
`efrac`	Upper limit of fraction failures in 'mppl'.
`calc.martres`	Should martingale residuals be calculated?
`control`	See `coxreg`
`verbose`	Should Warnings about convergence be printed?
`calc.hazards`	Deprecated. See `coxreg`.
`center`	Deprecated. See `coxreg`.

Details

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

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.

Note

It is the user's responsibility to check that indata is sane.

Author(s)

Göran Broström

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))

eha documentation built on Oct. 1, 2023, 1:07 a.m.