[R] "logistic" + "neg binomial" + ...

From: Ted Harding <Ted.Harding_at_nessie.mcc.ac.uk>
Date: Fri 22 Sep 2006 - 19:25:15 GMT


Hi Folks,

I've just come across a kind of problem which leads me to wonder how to approach it in R.

Basically, each a set of items is subjected to a series of "impacts" until it eventually "fails". The "force" of each impact would depend on covariates X,Y say; but as a result of preceding impacts an item would be expected to have a "cumulative frailty" such that the probability of failure due to a particular impact would possibly increase according to the series of impacts already survived.

Without the "cumulative frailty" one could envisage something like a logistic model for the probabiliy of failure at each impact, leading to a kind of generalised "exponential distribution" -- that is, the likelihood for each item would be of the form

  (1-P[1])*(1-P[2])*...*(1-P[n-1])*P[n]

where P[i] could have a logistic model in terms of the values of X[i] and Y[i], and n is the index of the impact at which failure occurred. That is then a solvable problem.

Even so, I'm not (so far) finding in the R resources the appropriate analogue of glm for this kind of model. I dare say a prolonged trawl through the various "survival" resources might lead to something applicable, but ...

And then there's the cumulative frailty ... !

Suggestions welcome!

With thanks,
Ted.



E-Mail: (Ted Harding) <Ted.Harding@nessie.mcc.ac.uk> Fax-to-email: +44 (0)870 094 0861
Date: 22-Sep-06                                       Time: 20:25:12
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