On Aug 23, 2009, at 10:14 AM, Brittany Hall wrote:
Hello,
I am fairly new to R and having a problem with the lme command. I
have searched on forums, read the Fox 2002 chapter, and R help, but
the suggestions that I have tried have not helped me.
My data file is called Acsdata.
This is my script:
Acsdata.1 <- lme(Acsdata$gsi ~ Acsdata$asitotal + Acsdata$famstrto +
as.factor(Acsdata$GEN) + Acsdata$asxfs + Acsdata$asxpar + Acsdata
$asxgp + Acsdata$asxfsxpa + Acsdata$asxfsxgp, random = ~1|Acsdata
$family)
I keep getting the error: object "gsi" not found. However, when I
use the summary function, R is able to recognize gsi.
I welcome any suggestions.
Thanks
Be sure that the Acsdata data frame is not attach()ed. That can cause
certain conflicts.
Then, be sure to utilize the 'data' argument that is available in R
functions that take formulae as arguments. So use:
Acsdata.1 <- lme(gsi ~ asitotal + famstrto + as.factor(GEN) + asxfs +
asxpar + asxgp + asxfsxpa + asxfsxgp,
random = ~1|family, data = Acsdata)
I also think that it would be 'cleaner' to coerce 'GEN' to a factor
before calling lme(). It results in more readable output from the
function and it's methods.
See 'An Introduction to R', available in your R distribution or online
at http://cran.r-project.org/manuals.html for general information on
using modeling functions.
Addtionally, as you progress through this, you may have follow on
questions and there is a focused R e-mail list on mixed models. See https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
for more information.
Finally, in addition to John's excellent book that you reference
above, the seminal reference for lme() is:
Jose C. Pinheiro and Douglas M. Bates
Mixed-Effects Models in S and S-Plus
Springer, 2000. ISBN 0-387-98957-0
HTH,
Marc Schwartz
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