rsmul {relsurv} | R Documentation |
Fits the Andersen et al multiplicative regression model in relative survival. An extension of the coxph function using relative survival.
rsmul(formula, data, ratetable = survexp.us, int,na.action,init, method,control,...)
formula |
a formula object, with the response on the left of a ~ operator, and
the terms on the right. The terms consist of predictor variables separated by
the + operator, along with a ratetable term. The ratetable term
matches each subject to his/her expected cohort. If the variables are organized and named
in the same way as in the population tables, the ratetable term can be omitted.
The response must be a survival object as
returned by the Surv function. The time must be in days.
|
data |
a data.frame in which to interpret the variables named in
the formula .
|
ratetable |
a table of event rates, such as survexp.us .
|
int |
the number of follow-up years used for calculating survival(the rest is censored). If missing, it is set the the maximum observed follow-up time. |
na.action |
a missing-data filter function, applied to the model.frame,
after any subset argument has been used. Default is
options()$na.action . |
init |
vector of initial values of the iteration. Default initial value is zero for all variables. |
method |
the default method mul assumes hazard to be constant on yearly intervals. Method mul1 uses the ratetable
to determine the time points when hazard changes. The mul1 method is therefore more accurate, but at the same time can
be more computationally intensive. |
control |
a list of parameters for controlling the fitting process.
See the documentation for coxph.control for details.
|
... |
Other arguments will be passed to coxph.control . |
an object of class coxph
.
Pohar M., Stare J. "Relative survival analysis in R." Computer Methods and Programs in Biomedicine, 81: 272-278, 2006.
Andersen, P.K., Borch-Johnsen, K., Deckert, T., Green, A., Hougaard, P., Keiding, N. and Kreiner, S. "A Cox regression model for relative mortality and its application to diabetes mellitus survival data.", Biometrics, 921-932, 1985.
data(slopop) data(rdata) rsmul(Surv(time,cens)~sex+as.factor(agegr)+ratetable(age=age*365, sex=sex,year=year),ratetable=slopop,data=rdata)