Re: ASReml: Enquiry for problem solving

Dear ASReml group,

Are there any instances, say for a general case, in which a trivariate
analysis where one is binomial (underlying scale) can be fit?
I ran two bivariate analyses, each fit a binomial trait (Trait 1) and one of
two continuous traits (Trait 2 or Trait 3), and then fit a trivariate model
(Trait 1, Trait 2, and Trait3) with constrained covariances. Results from
the pair of bivariate analyses compared to the trivariate were the same. My
question is, since the same results were produced when the covariances were
constrained, will the results from the trivariate model be meaningful when
allowing estimation of those covariances?

Kind Regards,
Devori Beckman

Devori W Beckman
Graduate Research Assistant
Animal Breeding & Genetics
Dept. of Animal Science, 229 Kildee Hall
Iowa State University  Ames, IA  50010

Phone:  208-521-1181
Office:  515-294-2712
Fax:  515-294-4850

Email: dbeckman_at_iastate.edu

On 3/11/08 11:49 PM, "arthur.gilmour_at_DPI.NSW.GOV.AU"
<arthur.gilmour_at_DPI.NSW.GOV.AU> wrote:

>
> Dear Hooi Ling,
>
> Please accept my apology for not replying yesterday.
>
> ASReml canot fit a trivariate analysis where one is binomial on the underlying
> scale.
>
> To fit a bivariate where one is binomial, you must specify the binomial trait
> first.
>
> Thus the following is more likely to run. (for lgiw and surv)
>
>
> surv lgiw !BINOMIAL ~ Trait at(Tr,2).(gen.env.line), #
> at(Tr,2).(gen.env.sex.line gen.env.sex.line.age_hv),
> at(Tr,1).(gen.env.line) !r -at(Tr,2).spl(age_hv) Tr.animal Tr.dam
>
> 1 2 2 # 1 set of resid,2 dim.anim.trait,Gstruc,Tr.anim.Tr.dam
> 0 # use all records
> Trait 0 US !GP
> 1
> .01 0.016
> # 2 traits,records,sorted,residual var1,cov12,var2
>
> Tr.animal 2 # 2 dim.struc,always 2
> Tr 0 US !GP
> 0.028
> 0.01 0.019
> # 2 traits,animal var1,cov12,var2
> animal
>
> Tr.dam 2 # 2 dim.struc,always 2
> Tr 0 US !GP
> 0.011
> 0.005 0.105 # 2 traits,dam var1,cov12,var2
> dam
>
> May Jesus Christ be gracious to you in 2008,
>
> Arthur Gilmour, His servant .
>
> Mixed model regression mapping for QTL detection in experimental crosses.
> Computational Statistics and Data Analysis 51:3749-3764 at
> http://dx.doi.org/10.1016/j.csda.2006.12.031
>
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>
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>> ><><><><><><><><><><><><><><><><><><><><><><><>
Received on Sat Mar 13 2008 - 13:23:53 EST