Fitting multivariate linear mixed model in R

Question

I'm wondering how to fit multivariate linear mixed model and finding multivariate BLUP in R. I'd appreciate if someone come up with example and R code. Thanks

Edit

I wonder how to fit multivariate linear mixed model with lme4. I fitted univariate linear mixed models with the following code:

library(lme4)
lmer.m1 <- lmer(Y1~A*B+(1|Block)+(1|Block:A), data=Data)
summary(lmer.m1)
anova(lmer.m1)

lmer.m2 <- lmer(Y2~A*B+(1|Block)+(1|Block:A), data=Data)
summary(lmer.m2)
anova(lmer.m2)

I'd like to know how to fit multivariate linear mixed model with lme4. The data is below:

Block A B    Y1    Y2
 1 1 1 135.8 121.6
 1 1 2 149.4 142.5
 1 1 3 155.4 145.0
 1 2 1 105.9 106.6
 1 2 2 112.9 119.2
 1 2 3 121.6 126.7
 2 1 1 121.9 133.5
 2 1 2 136.5 146.1
 2 1 3 145.8 154.0
 2 2 1 102.1 116.0
 2 2 2 112.0 121.3
 2 2 3 114.6 137.3
 3 1 1 133.4 132.4
 3 1 2 139.1 141.8
 3 1 3 157.3 156.1
 3 2 1 101.2  89.0
 3 2 2 109.8 104.6
 3 2 3 111.0 107.7
 4 1 1 124.9 133.4
 4 1 2 140.3 147.7
 4 1 3 147.1 157.7
 4 2 1 110.5  99.1
 4 2 2 117.7 100.9
 4 2 3 129.5 116.2

Thank in advance for your time and cooperation.

Answer 1

Try the R package nlme

You can find some examples, theory and further documentation in: http://cran.r-project.org/doc/contrib/Fox-Companion/appendix-mixed-models.pdf

The nlme package is able to calculate pooled estimates [or the so called BLUP= best linear unbiased predictor].

Once you've downloaded the package, type in R console: help(predict.lme)

For more information, look at page 17 in Fox's paper. There you can find an example on how to pool information across subjects.

Hope this helps :)