Dear ASREMLers,
Action on missing values depends on where they occur.
Missing values in independent variables and factors are treated as
zeros.
The manual says you may delete the whole record by specifying !D0
but I just tested it and it doesn't. I will rectify that
but in the meanwhile you will have to manually delete records with
missing values in independent variables if this is what you want
to happen. An alternative strategy which is sometimes appropriate
for covariates is to CENTRE the covariate - which is equivalent
to imputing the MEAN value to the missing value.
Concerning the dependent variable, ASREML drops records with
missing values unless the 'mv' term is included in the model
or the analysis is multivariate.
>
> A question about missing values.
> I thought asreml would recognize the star (*) as a missing value,
> However, in the following simple example, the program has taken it as a
> valid zero-value
> This in spite of the fact that one missing is given in the variable list.
>
>
> ------data--------
>
> 12 73
> 14 89
> 16 95
> 13 76
> * 97
>
> ------as file------
>
> test data to checking missing
> x
> y
> test.dat
> y ~ mu + x
>
> ----output---------
> ASREML [15 Feb 1999] test data to checking missing
>
> Wed May 12 10:14:14 1999 128.00 Mbyte test
> Reading test.dat FREE FORMAT skipping 0 lines
> Univariate analysis of y
> Using 5 records [of 5 read from 5 lines of test.dat
> ]
> Model term Size Type COL Minimum Mean Maximum #zero
> #miss
> 1 x 1 Covariat 1 12.00 13.75 16.00 0
> 1
> 2 y 1 Variate 2 73.00 86.00 97.00 0
> 0
> 3 mu 1 Constant Term
> Forming 3 equations: 3 dense
> Initial updates will be shrunk by factor 0.548
> LogL=-12.2458 S2= 139.17 3 df 1.0000
> Final parameter values 1.0000
>
> Source Model terms Gamma Component Compnt/StndErr
> Variance 5 3 1.00000 139.167 1.22 P
> Solution Standard Error T-value T-prev
> 1 x 1 0.45 0.45 [DF F_inc F_all]
> 1 -0.625000 0.932626 -0.67
> 3 mu 1 265.72 64.82 [DF F_inc F_all]
> 2 92.8750 11.5359 8.05
> Finished: Wed May 12 10:14:14 1999 LogL Converged
>
>
>
> 2 more:
>
> I was originally wondering whether records with missing covariates of
> fixed effect codes are discarded, I suppose they are.
NOT unless you deliberately discard them
>
> How is the log likelihood calculated? Is it not
> logl=-.5*N*log(2*pi)-.5*log(det(V))-.5*(e'*inv(V)*e)
> but this gives me logl = -18.4339
>
The formula in Chapt 2 says
-0.5(log | X'HX | + log|H| + e log S2 + yPy/S2)
This is parameterized differently from yours but some terms are equivalent.
In your example H=I and X'X = 765 55
55 5 from .asl file
So LogL is -0.5 ( 6.6846 + 0 + 3 x 4.9357 + 3 ) = 12.2458
My expression omits the pi term but includes a term in X
regards
Arthur
> julius
> ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
> Julius van der Werf e-mail:jvanderw@metz.une.edu.au
> Sr. Lecturer in Animal Genetics www:
http://metz.une.edu.au/~jvanderw/
> Division of Animal Science phone: +61-2-6773-2092
> School of Natural Resources and Rural Science fax : +61-2-6773-3275
> University of New England home : +61-2-6775-2442
> Armidale, NSW 2350, AUSTRALIA
> +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
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Arthur Gilmour PhD mailto: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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