Re: Your Message Sent on Tue, 12 May 1998 12:13:35 +1100
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Re: Your Message Sent on Tue, 12 May 1998 12:13:35 +1100



Dear James,
I'm a bit slow!  You are over the TASMAN.

There is no problem with your coding.

Explanation of parameter values printed out is:

When ASREML sees
a model    ~ sex age !r animal dam ide(dam) !f cg
It initializes the first 6 positions in the vector of parameters
so ide(dam) is in cell 5 and  cg in cell 6 [its value is zero since it
is a fixed effect]

Then ASREML alolocates a cell for the error variance [7] and then for
the US structure [animal dam] cells 8-10.

What is printed in the LogL lines is cells 5 - 10 of this vector
so that explains where the zero comes from.

In the printout of variance parameters, the redundant [undefined] positions
are ignored.

When it comes to the .pin file, the defoned terms are taken from the
>    Source       Model  terms     Gamma     Component    Compnt/StndErr
>   ide(dam)      27066   7268  0.147784      0.147784          6.57
>   animal      US=UnStr     1 -0.766052E-02 -0.766052E-02     -2.69
>   animal      US=UnStr     1 -0.111642E-02 -0.111642E-02     -0.17
>   animal      US=UnStr     2  0.278432E-01  0.278432E-01      1.39

table so only 4 items are defined.  [Conseqently the .vvp file shp`ould
have only 10 values.]

You are correct in interpreting the components 

However, you now catch me out.  Because the Variance of 1 is not in this table,
there is no way of including it in the .pin file calculations [ I do not
have a sysntax for addind a constant to a variance] other than
appending a 5th row
    Residual       0         0     1.           1.                0.
    
    
    to the table in the .asr file and appending 5 zeros to the .vvp file.
    
    I'll address this deficiency.
    
    
    Concerning the analysis you have done, It seems you probably have no
    direct genetic effects on survival, only maternal ones.
    
    
    Arthur
    
> 
> Arthur,
> 
> I feel a bit silly having to write to you again, I have almost got the asreml 
sorted out but have
> one or two little questions. Please feel free to put the reply on the ASREML 
list if you do not
> think the question is too silly and may help someone else. BTW you were right 
before with the
> previous question I had - we had one errant animals missing from our ped file.
> 
> I am using the following input file:
> 
> computer> :more sup1.as
> ASREML analysis of surv at 48 hrs old 
>  animal   !P
>  sex    2 !A
>  age   10 !A
>  cg     18 !A
>  dam       !P                           # has genetic group codes in here too 
so no missing dams 
>  LS48   1 !M-1.00                  # coded as 0 = dead  1 = alive   -1.00 = 
missing
> ped.dat !GROUPS 43
> data.dat
> LS48 !bin !probit ~ sex age !r animal dam ide(dam) !f cg
> 0 0 1
> animal 2
> 2 0 US 0.3 0.0 0.3
> animal
> computer>:
> 
> I am using probit because the Logit does not converge ?? but the probit does
> The model i am trying to fit is
> LS = sex  + dam_age + contemp_group + additive genetic + maternal genetic + 
dam
> permanent environment (random)
> 
> With the output I get :
> 
> computer> :more sup1.asr
>   ASREML [16 Apr 1998]  ASREML analysis of surv data
> 
>  Thu May  7 17:58:54 19981024.00 Mbyte    sup1.asr
> 
>  A-inverse retrieved from ainverse.bin
>  PEDIGREE [ped.dat ] has    27066 animals,   95949 Non zero elements
>   Reading data.dat  FREE FORMAT skipping 0 lines
>  Univariate analysis of LS48
>  Using    22703 records [of   22703 read from   22703 lines of data.dat
>    ]
>   Model term      Size Type    COL   Minimum    Mean      Maximum   #zero 
#miss
>    1 animal      27066 Direct    1   3985.    0.1541E+05 0.2707E+05     0     
0
>    2 sex             2 Factor    2      1     1.4969          2         0     
0
>    3 age            10 Factor    3      1     2.0807         10         0     
0
>    4 cg             18 Factor    4      1     8.4273         18         0     
0
>    5 dam         27066 Direct    5   45.00     7609.     0.2326E+05     0     
0
>    6 LS48            1 Variate   6  1.000     0.8884      1.000      2533     
0
>    7 ide(dam)    27066 Factor    5     45  7608.8208      23264         0     
0
>      2  US=UnStr    0.30    0.00    0.30
>  27066  Ainverse
>  Structure of animal       has   54132 levels defined
>   Forming 81229 equations: 13 dense
>  Initial updates will be shrunk by factor    0.010
>  Data distribution and link: Binomial; Probit P=Normal Integral(XB)
>        Deviance adjust= -19139.432356986621
>  NOTICE: 19845 (more) singularities,
>  LogL=-23519.1     S2=  1.000     22651 df   0.10000   0.00000   1.00000
>      0.30000   0.00000   0.30000
>        Deviance adjust= -11356.4644239385
> LogL=-22110.3     S2=  1.000     22651 df   0.14888   0.00000   1.00000
>     -0.00766  -0.00112   0.02789
>        Deviance adjust= -13120.537311384705
>  NOTICE: 19846 (more) singularities,
>  LogL=-22071.9     S2=  1.000     22651 df   0.14806   0.00000   1.00000
>     -0.00767  -0.00111   0.02784
>        Deviance adjust= -13131.675942170163
>  LogL=-22082.8     S2=  1.000     22651 df   0.14779   0.00000   1.00000
>     -0.00766  -0.00111   0.02784
>  Final parameter values                      0.14778   0.00000   1.00000
>     -0.00766  -0.00112   0.02784
>  Variance heterogenity factor     0.58
> 
>    Source       Model  terms     Gamma     Component    Compnt/StndErr
>   ide(dam)      27066   7268  0.147784      0.147784          6.57
>   animal      US=UnStr     1 -0.766052E-02 -0.766052E-02     -2.69
>   animal      US=UnStr     1 -0.111642E-02 -0.111642E-02     -0.17
>   animal      US=UnStr     2  0.278432E-01  0.278432E-01      1.39
>                      Solution       Standard Error    T-value     T-prev
>    2 sex                      1        9.02        9.02 [ DF F_inc F_all ]
>  M                     -0.706125E-01   0.235071E-01     -3.00
>    3 age                      8        6.50        6.54 [ DF F_inc F_all ]
>  03                     0.191854       0.354455E-01      5.41
>  04                     0.628799E-01   0.511734E-01      1.23     -3.14
>  05                     0.278776E-01   0.676825E-01      0.41     -0.55
>  06                    -0.322999E-01   0.951852E-01     -0.34     -0.65
>  07                    -0.184251       0.189072         -0.97     -0.79
>  08                     0.363875       0.307400          1.18      1.64
>  10                     0.117837E-01    5257.86          0.00
>  01                      1.31682       0.379077          3.47      0.00
>    1 animal               27048 effects fitted
>    5 dam                  27039 effects fitted
>    7 ide(dam)              7268 effects fitted
>    4 cg                      18 effects fitted
>  1881 possible outliers: see .res file
>  Finished: Thu May  7 19:32:46 1998   LogL Converged
> computer> :
> 
> 
> now I am confused as to the order that these effects are being fitted:
> ie
>  Final parameter values                      0.14778   0.00000   1.00000
>     -0.00766  -0.00112   0.02784
> 
> I assumed the 0.14778 is the dam pe effect (not augmented with NRM)
> I have no idea what the 0.0000 is ?????
> The 1.000000 is the error variance which is fixed to 1.00000 automatically 
with the !bin 
> ie !s2=1.00
> The -0.00766  is the add genetic
> The  -0.00112   is covariance between add genetic and maternal genetic
> The   0.02784 is the mat genetic effects
> 
> So what is the 0.00000   effect ?
> Have I mucked up the model specs to create this bogus random term?
> And what are the order numbers of the variance components so I can make up a 
sensible .pin
> file to calculate correlations etc?
> Should the .pin be set up as per usual with a residual variance of 1.00 to 
give standard
> heritability and rgs on the transfromed scale?
> And finally what do the Compnt/StndErr 's mean on the transformed scale?
> 
> Many thanks and terribly sorry to bother you again.
> 
> skerry
> 
> --
> PLEASE NOTE NEW EMAIL ADDRESS BELOW
> *****************************************************
> James Wilfred Skerritt                             
>     ()()          Visiting Scientist (Genetics Unit)
>     (..)          Landcorp Farming Limited                     
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> snail: Landcorp Farming Ltd    
>        PO Box 1235,              _--_|\
>        Hamilton,New Zealand     /      \   
> Home:  43B Hibiscus Avenue,     \_.--._/    /|
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> *****************************************************
> Augustine says (De Doctr. Christ. i, 32), "Because He is good, we are."
> 


<><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><>
Arthur Gilmour PhD                    email: Arthur.Gilmour@agric.nsw.gov.au
Senior Research Scientist (Biometrics)                 fax: <61> 2 6391 3899
NSW Agriculture                                             <61> 2 6391 3922
Orange Agricultural Institute               telephone work: <61> 2 6391 3815
Forest Rd, ORANGE, 2800, AUSTRALIA                    home: <61> 2 6362 0046

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