I think you are replying to Dr Therneau without including this context:
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Survreg produces MLE estimates.

For your second question, don't know what you are asking.  Can you be
more specific and detailed?

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Do you know if the parameters estimators are MLE estimators?

One more question:
In my case study I have failures that occured on different objects that have different age and length, could I use weight to find the estimates of a weibull law and so to find the probabilty of failure per unit of length
for example?
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On Sep 6, 2011, at 9:50 AM, Boris Beranger wrote:

Sorry when we talk about about MLE estimates does that mean WLE?I am trying to understand if the survreg function is allowing a weight for each density
function when calculating the likelihood.

In my second question I was trying to explain that my problem is that I have pipes of different length and I want to know their probability to break per
metre. My idea was to weight each of my observations to get estimate
probabilities per metre.Does that sound realistic?

I have generally used Poisson regression [ glm(..., family="poisson") ] in that situation. It lets you do two things: a) apply weighting by using offset=log(length_of_pipe) and b) model multiple breaks in a pipe if such an occurrence is possible. (It also produces an MLE estimate if that feature is of some special importance.)

I respectfully defer to anything Dr Therneau says on this matter and am only really posting in hopes that he will clarify whether there is any value in thinking about the use of offset terms in either parametric or Cox survival models.

There is an offset argument in glm but I do not see one (any longer?) in survreg or coxph. I have what must be an extremely vague memory of seeing an offset term in coxph formulas, but I do not see such a possibility described in the current help pages. Therenau and Grambsch indicates that CPH models with certain forms of frailty are similar to models with offsets but the help apge for `Surv` specifically warns against the use of "gamma/ml or gaussian/reml [frailty terms] with survreg".

--

David Winsemius, MD
West Hartford, CT

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