To all ASREML users,
I am currently doing my phD at The University of
Adelaide. My project involves analysing fleece and skin measurements
taken from the South Australian Turretfield Research Flock.
We have a situation in which there are approximately 15 skin traits and
20 fleece traits, with which we want to calculate between trait
correlation values.
We have already conducted bivariate analysis amongst these traits, and we
are wanting now to calculate some multivariate correlation values. The
memory on our computer restricts us to 11 traits per run, and there are
certain traits that cannot be grouped together because it appears as if
LogL will not converge when traits that are highly correlated are grouped
together.
We would like some comments and advice, based on other users experience,
on how to logically group our traits. Should we aim to get as many
traits in a run as possible, or should we make more groups with smaller
numbers? Is there a point when you stop increasing the number of traits
included in a particular run? Are there certain traits that should be
grouped together to obtain the most accurate correlation values?
These are a few of our questions, can users reply with details on what
method they have used to calculate multivariate correlation values
amongst large data sets.
Thank-you,
Jane Hill
The University of Adelaide
South Australia.