Brian,
What about creating the covariance matrix with the help of the kronecker
product? For instance, suppose your intercepts are ~ N(0,var1) and your
residual errors are ~ N(0,var2). Suppose further that you want 10
clusters of 5 observations each. I believe you can create the overall
covariance matrix with kronecker(diag(10),matrix(var1,5,5)) +
var2*diag(50). This can then be fed as the variance to the mvtnorm
function. Hope this helps.
Regards,
-Cody
-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Brian Perron
Sent: Tuesday, July 11, 2006 15:59 PM
To: r-help at stat.math.ethz.ch
Subject: [R] generating clustered data
Hello R folks,
Does anybody have code to share for generating (via simulation)
clustered data? The type of data I am looking to simulate would allow
fitting of a multilevel model with random intercepts. I looked at the
mvtnorm package but am not quite sure how to create clusters. (Can this
be done by simply changing the seed?) If somebody could point me where
to look for the relevant code or perhaps send some sample code, that
would be great.
Thanks,
Brian
______________________________________________
R-help at stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide!
http://www.R-project.org/posting-guide.html
This e-mail, facsimile, or letter and any files or attachmen...{{dropped}}