Re: Asreml for phenotypic plasticity

Dear Mellissa

I agree with Brian.
Try the following coding to allow a correlation between slope and
intercept:

PD ~ mu AGE sCONES !r !{ newid CONES.newid !} DAM YR Byear
0 0 1

newid 2
2 0 US !GP
0.2
0.001 0.01
newid 0

The analysis will be on the GAMMA scale so the variance components are
relative rather than absolute.

The .sln file should have an intercept and slope for each 'newid'

You have defined AGE as a FACTOR with !A which is likely to have its
levels in an unnatural order.

I imaging making CONES a factor and interacting it with newid might just
generate a term equivalent to the residual
unless there are multiple observations for an individual with the same
value for CONES

The F-statitics do relate to Wald tests. ASReml2 will often be able to
calculate the residual degrees of freedom
to complete the F-test but ASReml1.1 cannot.

I'm unclear what your are plotting from the .yht file. Residual vs Fitted
value??
I would not expect to see a relationship unless you have a pedigree on
newid
in which case it would be an artefact of the model.

 Check out http://www.cargovale.com.au/
for my personal greetings and update.

I thank God for His mercy through Jesus Christ.

Arthur Gilmour PhD
mailto:Arthur.Gilmour_at_dpi.nsw.gov.au
Principal Research Scientist (Biometrics)
NSW Department of Primary Industries
Orange Agricultural Institute, Forest Rd, ORANGE, 2800, AUSTRALIA

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You wrote:
Hi all,
I am trying to analyse variation in phenotypic plasticity using Asreml. I
have
multiple measurements of parturition date for ~270 females, and I am using
the
interaction between food abundance (CONES) and individual identity as the
slope
of the reaction norm (i.e. CONES.newid). I find I get quite different
answers
in the asr file if I used standardised cones (centred on zero). Should
this be
the case?

Also, I find I have only one estimated effect size for CONES in the sln
file,
although AGE (also a fixed effect) has an effect size for each age
presented.
Would making CONES a factor change this?

I would also like to know how the analysis of variance presented in the
asr file
relates to Wald stats (if it does!). Can I use this to compare models with
different fixed effects?

Finally, I find no significant variation in phenotypic plasticity - but
when I
plot the values from the yht file for the best-fitting model, it looks as
though there is significant variation. Can anyone suggest why this would
be?

My job file is as follows:
 newid !P #identity of individual
 YR !A #year of parturition
 AGE !A #age of individual
 CONES #measure of food abundance
 PD #parturition date in Julian days
 DAM !P #identity of individual's mother
 sCONES #standardised cone number
 sAGE #standardised age of individual
 Byear !A #birthyear of individual
!MVREMOVE !MAXIT 1000
PD ~ mu AGE sCONES !r newid DAM CONES.newid YR Byear
1 1 5 !STEP 0.001
0 0 IDEN 382

newid 1
newid 0 IDV 56

DAM 1
DAM 0 IDV 21

CONES.newid 2
CONES 0 US !GP
1.5
newid

YR 1
YR 0 IDV 21

Byear 1
Byear 0 IDV 21 #!GP

Thanks in advance for any suggestions.
Melissa

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Received on Tue Mar 30 2006 - 17:34:09 EST