Regression for a Parametric Survival Model

DESCRIPTION:

Fit a survival model using parametric regression.

USAGE:

survReg(formula, data=sys.parent(), weights, subset, na.action, 
     dist="weibull", init, scale=0, control, 
     model=F, x=F, y=T, ...) 

ARGUMENTS:

formula
a formula expression as for other regression models. See the documentation for lm and formula for details. The response must be the output from the Surv function.

OPTIONAL ARGUMENTS:

data
optional data frame in which to interpret the variables occurring in the formula.
weights
a vector of observation weights, with length equal to the number of observations. Weights must be nonnegative and it is strongly recommended that they be strictly positive. Observations that are to be excluded from the fit should be specified using the subset argument.
subset
subset of the observations to be used in the fit.
na.action
function to be used to handle any NAs in the data. Use na.action=na.exclude to fit the model without NAs, but pad the returned components of residuals and fitted values to the length of the original data.
dist
assumed distribution for y variable. Allowed values include "weibull", "exponential", "gaussian", "logistic", "lognormal" and "loglogistic". If the argument is a character string, then it is assumed to name an element from survReg.distributions (enter names(survReg.distributions) for a full list of choices). Otherwise, it is assumed to be a user defined list conforming to this standard.
parm
a list of fixed parameters. For the t-distribution for instance this is the degrees of freedom; most of the distributions have no parameters.
init
optional vector of initial values for the parameters.
scale
optional fixed value for the scale. If set to <=0 then the scale is estimated.
control
a list of control values, in the format produced by survReg.control.
model
if TRUE, the model frame is returned.
x
if TRUE, then the X matrix is returned.
y
if TRUE, then the y vector (or survival times) is returned.
...
other arguments which will be passed to survReg.control.

VALUE:

an object of class "survReg" is returned.

NOTE:

The survReg function is the successor to the survreg function from survival4.

COMPUTATION:

The routine uses a Newton-Raphson iteration with step halving, with provision for general penalized term. Fisher scoring is used for intermediate steps where the information matrix is not positive definite.

SEE ALSO:

EXAMPLES:

survReg(Surv(futime, fustat) ~ ecog.ps + rx, data=ovarian, dist='lognormal')