My question was how can we estimate effects and define correct
model equivalent to SAS code provided.

On Fri, Apr 15, 2011 at 10:21 PM, Nilaya Sharma <nilaya.sharma@gmail.com>wrote:

> Hi R community,
>
> I am new bird to R and moved recently from SAS. I am no means expert on
> either but very curious learner. So your help crucial for me to learn R.
> I have already got positive expression.
>
> I was trying to fit a mixed model in animal experiment but stuck at simple
> point. The following similar example is from SAS mixed model pp 212.
>
> # data
>
> genetic_evaluation <- read.table(textConnection("
> sire dam adg
> 1  1  2.24
> 1  1  1.85
> 1  2  2.05
> 1  2  2.41
> 2  1  1.99
> 2  1  1.93
> 2  2  2.72
> 2  2  2.32
> 3  1  2.33
> 3  1  2.68
> 3  2  2.69
> 3  2  2.71
> 4  1  2.42
> 4  1  2.01
> 4  2  1.86
> 4  2  1.79
> 5  1  2.82
> 5  1  2.64
> 5  2  2.58
> 5  2  2.56"), header = TRUE)
>
> # my R practice codes
> require (lme4)
>  lmer(adg ~ 1 + (1|sire) + (1|dam/sire), data=genetic_evaluation)
>
>  ****error message********************************************88
>  Error: length(f1) == length(f2) is not TRUE
> In addition: Warning messages:
> 1: In sire:dam : numerical expression has 20 elements: only the first used
> 2: In sire:dam : numerical expression has 20 elements: only the first used
>
> **********************how can I estimate the BLUP effects?*************
> #equavalent code in SAS
> proc mixed data=genetic_evaluation;
>    class sire dam;
>    model adg= / ddfm=kr;
>    random sire dam(sire);
>    estimate 'sire 1 BLUP "broad" '
>             intercept 1 | sire 1 0;
>    estimate 'sire 1 BLUP "narrow" '
>             intercept 2 | sire 2 0
>             dam(sire) 1 1  0 0  0 0  0 0  0 0  / divisor=2;
>    estimate 'sire 1 BLUP with dam 1'
>             intercept 1 | sire 1 0
>             dam(sire) 1 0;
>    ods select CovParms Estimates;
> run;
>
> # Estimate statement define predictable functions. All fixed effect
> cofficient must appear first and then random effect coefficients. The fixed
> and random
> #effect cofficient are seperated by |
>
> ****************Expected outputs according to SAS
> *************************************
>                       Estimate
> sire 1 BLUP "broad    2.2037
> sire 1 BLUP "narrow"  2.1609
> sire 1 BLUP with dam1 2.1002
>
>  Data details:
> The data is animal science data in which five sires were randomly sampled
> from the population and were randomly mated with two dams.
> Two offspring per sire dam combination were measured. Average daily gain
> was recorded. We are interested in breeding value of ith sire(means that
> which
> gives offsprings with higher gain
>
> NIL
>

	[[alternative HTML version deleted]]

