rstrans: Fit Cox Proportional Hazards Model in Transformed Time

rstransR Documentation

Fit Cox Proportional Hazards Model in Transformed Time

Description

The function transforms each person's time to his/her probability of dying at that time according to the ratetable. It then fits the Cox proportional hazards model with the transformed times as a response. It can also be used for calculatin the transformed times (no covariates are needed in the formula for that purpose).

Usage

rstrans(formula, data, ratetable, int,na.action,init,control,rmap,...)

Arguments

formula

a formula object, with the response as a Surv object on the left of a ~ operator, and, if desired, terms separated by the + operator on the right.

NOTE: The follow-up 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 slopop.

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.

control

a list of parameters for controlling the fitting process. See the documentation for coxph.control for details.

rmap

an optional list to be used if the variables are not organized and named in the same way as in the ratetable object. See details below.

...

other arguments will be passed to coxph.control.

Details

NOTE: The follow-up time must be specified in days. The ratetable being used may have different variable names and formats than the user's data set, this is dealt with by the rmap argument. For example, if age is in years in the data set but in days in the ratetable object, age=age*365.241 should be used. The calendar year can be in any date format (date, Date and POSIXt are allowed), the date formats in the ratetable and in the data may differ. A side product of this function are the transformed times - stored in teh y object of the output. To get these times, covariates are of course irrelevant.

Value

an object of class coxph. See coxph.object and coxph.detail for details.

y

an object of class Surv containing the transformed times (these times do not depend on covariates).

References

Method: Stare J., Henderson R., Pohar M. (2005) "An individual measure for relative survival." Journal of the Royal Statistical Society: Series C, 54 115–126.

Package. Pohar M., Stare J. (2006) "Relative survival analysis in R." Computer Methods and Programs in Biomedicine, 81: 272–278

Relative survival: Pohar, M., Stare, J. (2007) "Making relative survival analysis relatively easy." Computers in biology and medicine, 37: 1741–1749.

See Also

rsmul, invtime, rsadd, survexp.

Examples

data(slopop)
data(rdata)

#fit a Cox model using the transformed times
#note that the variable year is given in days since 01.01.1960 and that 
#age must be multiplied by 365.241 in order to be expressed in days.
fit <- rstrans(Surv(time,cens)~sex+as.factor(agegr),rmap=list(age=age*365.241,
        sex=sex,year=year),ratetable=slopop,data=rdata)


#check the goodness of fit
rs.br(fit)

relsurv documentation built on March 18, 2022, 5:15 p.m.

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