[R-sig-eco] Are likelihood approaches frequentist?
Rubén Roa-Ureta
rroa at udec.cl
Mon Sep 29 18:29:30 CEST 2008
prado wrote:
> Thanks, Rubén
>
> My point with this topic was to clarify that the likelihood-based
> approach is a distinct paradigm in statistical inference, and there is
> people in biology applying it successfully.
It's a very good point to make. Another important paper is Rubin's paper
on missing data: Biometrika 63:581-592, 1976. There Rubin basically
shows that it is easier to make statistical models for data with
Bayesian and likelihoodist inference, because the mechanism generating
missing data can be ignored if the missing data is missing at random,
whereas in sampling distribution inference this conditions is not
sufficient. To ignore the mechanism generating missing data it is also
necessary that the observed data be observed at random. Many usual
scientific studies involve missing data, such s random sampling from
finite populations, randomized experimental set up, etc.
>
> I agree with you that this point should be better stressed, specially
> for biologists. Taper & Lelle "The Nature of Scientific Evidence"
> (Chigago Univ Press, 2007) is a great help in this respect.
Thanks for this reference. I've missed it.
>
> Could you indicate the best works by Nelder Lindsey that could
> contribute to this point?
In the case of Nelder, I only know of his personal statement in the
quote that I gave by mistake in my first post, complemented in the
second post.
Lindsey has a very interesting paper in The Statistician (apart from
heresies): Relationship between sample size, model selection and
likelihood regions, and scientifically important differences. The
Statistician 48:401-411.
Regards
Rubén
More information about the R-sig-ecology
mailing list