mlreg.fit {eha}R Documentation

ML proportional hazards regression

Description

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

Usage

mlreg.fit(X, Y, rs, strats, offset, init, max.survs,
method = "ML", boot = FALSE, control)

Arguments

X The design matrix.
Y The survival object.
rs The risk set composition. If absent, calculated.
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 "ML" (default) or "MPPL".
boot No. of bootstrap replicates. Defaults to FALSE, i.e., no bootstrapping.
control See coxreg

Details

See mlreg for details.

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 sample, if requested on input.
conver TRUE if convergence.
fail TRUE if failure.
iter Number of performed iterations.

Note

rs is dangerous to use when NA's are present. It is the user's responsibility to ensure that indata is sane.

Author(s)

Göran Broström

References

~put references to the literature/web site here ~

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))

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

[Package eha version 0.98-0 Index]