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