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

[(Ted Harding)]

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.

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Date: 22-Sep-06                                       Time: 20:25:12
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