[R] Survival Analysis and Predict time-to-death

[survivalUser]

Dear All,

I would like to build a model, based on survival analysis on some data, that
is able to predict the /*expected time until death*/ for a new data
instance.

Data
For each individual in the population I have the, for each unit of time, the
status information and several continuous covariates for that particular
time. The data is right censored since at the end of the time interval
analyzed, instances could be still alive and die later.

Model
I created the model using R and the survreg function:

lfit <- survreg(Surv(time, status) ~ X) 

where:
- time is the time vector
- status is the status vector (0 alive, 1 death)
- X is a bind of multiple vectors of covariates

Predict time to death
Given a new individual with some covariates values, I would like to predict
the estimated time to death. In other words, the number of time units for
which the individual will be still alive till his death.

I think I can use this:

ptime <- predict(lfit, newdata=data.frame(X=NEWDATA), type='response')

Is that correct? Am I going to get the expected-time-to-death that I would
like to have?

In theory, I could provide also the time information (the time when the
individual has those covariates values), should I simply add that in the
newdata:

ptime <- predict(lfit, newdata=data.frame(time=TIME, X=NEWDATA),
type='response')

Is that correct? Is this going to improve the prediction? (for my data, the
time already passed should be an important variable).

Any other suggestions or comments?

Thank you!



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