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Antonio Hervas Abad wrote:

> I'm working with scallop (pecten maximus) stock assessment in Ireland.  One
> of the stock assessment procedures that i am carrying on is a sampling
> programm from the landings.  Shell height is recoreded from each landing.
> After several measurements from differents vessels, differents fishing
> areas and different time of the year i want to study the effect of vessels,
> season and location, on the scallop size structure obtained from the
> sampling.  I understand that analysis of variance (ANOVA or MANOVA) is the
> method to use for this study but maybe some of you has experience working
> with similars studies and can advice to me of which statistic analysis is
> the more suitable.


An interesting piece of research and one that I would like to see
repeated with Placopecten magellanicus on this side of the northwest
Atlantic!

However, the various replies to date, with their recommendation of using
  a Generalized Linear Model, all appear (to me) to face a problem that
Antonio's ANOVA would also face. That is, each observation would have to
comprise a single value for shell height, whereas the data are more
likely to take the form of a shell-height frequency.

Can GLM cope with that extra dimension in the data, treating the
frequency as a frequency? That would be ideal, if it can be done.

Or would it be necessary to treat the abundance of each size-class as a
separate independent variable and then use some GLM analogue of MANOVA?
Should the model use individual shell heights as replicates, nested
within samples (maybe one sample per landing)? Or would one have to
reduce each frequency to a mean and analyze just the means? It would
seem that any of those latter options would lose a lot of the
information in the original data.


Trevor Kenchington


--
Trevor J. Kenchington PhD                         [log in to unmask]
Gadus Associates,                                 Office(902) 889-9250
R.R.#1, Musquodoboit Harbour,                     Fax   (902) 889-9251
Nova Scotia  B0J 2L0, CANADA                      Home  (902) 889-3555

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