Re: Is my model right for survival rate?

Dear arthur.glimour:
First, thanks for your detailed answer and Suggestion.

arthur.gilmour_at_DPI.NSW.GOV.AU 写道:
> Dear luan sheng
>
> re:
> I am the beginner of asreml. I am estimating the variance of survival
> rate which is from the challenge test data of turbot. Turbot is one of
> marine fishies.
> this is my model:
> survival !bin !probit !wt=0 ~ mu !r animal fullsib 0.2
> Is the model right for this analysis? which is right for survival rate
> logit or probit link function?
> The format of data file is just like this:
> animal Sire Dam fullsib survival (binary,0 for death, 1 for survival)
> 20070028 2006041 20060159 3 0
> 20070029 2006041 20060159 3 0
> 20070030 2006041 20060159 3 0
> 20070031 2006041 20060159 3 0
>
> I strongly suggest you also fit a sire model, and compare the results,
> as the animal model can give biassed estimates of the variance with
> binomial data.
>
Using the sire model, the heritability is 0.1542±0.1169; using dam
model, the heritability is 0.1355±0.1245; using the animal model , the
value is 0.0598±0.049. I don't know which model is more exact. How to
test these model?

the following is my parameter file:

2007 survival rate analysis of challenge test of wssv by animal ,sire or
dam model
animal !P
sire !P
dam !P
fullsib 45 !I
tank 3 !I
survival

wssv2007.ped !MAKE
wssv20071h.dat !SKIP 1 !MAXIT 200

#Animal model
survival !bin !probit ~ mu tank !r animal fullsib 0.25
#sire model
survival !bin !probit ~ mu tank !r sire fullsib 0.25
#Dam model
survival !bin !probit ~ mu tank !r dam fullsib 0.25

for animal model, the .pin file is:

F PhenotypeVariance 1+2+3
H H2 2 4
H C2 1 4

for sire and dam model, the .pin file is:

F PhenotypeVariance 1+2+3
F sireordam4 2*4
H H2 5 4
H C2 1 4

By the way, I often see from the examples that the model line has one
numeric value at the last, just like this model, the value "0.25". I
can't find the notes about this from the user guide. I think it is the
prior residual variance, is right?

> In this case, you appear to have large families so it might be fine.
>
> survival !bin !probit !wt=0 ~ mu !r Sire fullsib 0.2
>
> I cannot tell from the data whether Sire and Dam provide the same grouping
> of records
> (i.e. you only have full sib families). If you have half sib families,
> then also\
> fit Dam.
>
>
All the families are half-sib families. The number of families were 40.
Each family about includes thirty animals.
> As a new user, you should try several forms of the models to get a feel
> for how models compare. e.g. You can also fit the models as if the
> traits were
> normal. Your model is simple, and appears to have an incidence around 50%
> so a Normal analysis should be consistent with the binary analysis.
>
>
If one trait is as Normal distribution in the theory, but Normal test is
significant and don't fit for normal distribution. Can these data be
used to estimate the heritability by animal model or other model ? or we
transformed the data by logarithm or square root, then use the data
transformed to estimated heritability, is right?
> For binary data, you can omit the '!wt=0' qualifier as 0 is the default
> setting.
>
>
>
>
> May Jesus Christ be gracious to you,
>
> Arthur Gilmour, His servant .
>
> Mixed model regression mapping for QTL detection in experimental crosses.
> Computational Statistics and Data Analysis 51:3749-3764 now available at
> http://dx.doi.org/10.1016/j.csda.2006.12.031
>
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>
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> Principal Research Scientist (Biometrics)
> NSW Department of Primary Industries
> Orange Agricultural Institute, Forest Rd, ORANGE, 2800, AUSTRALIA
>
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--
   Yours sincerely,
   luan sheng
   ----------------------------------------
   Yellow Sea Fisheries Research Institute
   Chinese Academy of Fisheries Sciences
   Nanjing Road 106
   Qingdao 266071
   China
   luansheng_at_gmail.com
   luansheng_at_ysfri.ac.cn
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