On Jun 22, 2009, at 12:35 PM, francogrex wrote:
Hello, I have this generalized linear formula:
log(x[i]/n[i])=log(sum(x)/sum(n)) + beta[i]
where the the x[i] and the n[i] are known.
Is there a way to program the GLM procedure to input the formula
above and
get the beta[i] estimates? If not the GLM is there another procedure
to do
that? The aim also afterwards is to estimate the profile-likelihood
CIs for
the beta parameters.
Not as stated. That would be expecting R to have symbolic algebraic
capabilities. Maybe next year^Wdecade?
That model is equivalent to:
log(x[i]/n[i])=log(sum(x)) - log(sum(n)) + beta[i]
So you could use a no-intercept model with log link in glm() and an
offset term for the first two terms of the r.h.s.
probi <- (x[i]/n[i])
glm(probi ~ 0 + offset(log(sum(x)) - log(sum(n) ), family=poisson)
--
David Winsemius, MD
Heritage Laboratories
West Hartford, CT
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