Thank you Giulia, for your response.

I am still having trouble, though, because I am struggling to shift my
random effects structure from lme4 to nlme. My dataset include 50 teams of
individuals with 5 people on each team. Each individual rated her team
members on  three dimensions of trust, which constitutes my multivariate
response. So each individual is both a respondent and a referent. These
rating were taken at three points in time. My random effects structure in
lmer for just one of the three response variables is:

model <- lmer(y1~1 + time + (1+time|respondentID) + (1+time|referentID) +
(1|dyadID) + (1|teamID))

teamID is the largest grouping, so observations are considered independent
across teams. dyadID represents the coupling of two people regardless of
whether they are the respondent or referent. dyadID is nested in teamID.
respondentID and referentID have a crossed structure that is nested within
teamID. respondentID and referentID also include random slopes.

lmer does an excellent job of creating the correct random effects
structure, but I am having a very difficult time setting it up in nlme. I
followed this post for setting up the crossed structure of respondentID and
referentID in nlme:

https://stat.ethz.ch/pipermail/r-help/2003-November/042647.html

However, I haven't figured out how to add the random slopes and other
random parameters. If I can get my random structure ported from lmer to
nlme, then I can work on adding the seemingly unrelated regression
structure next.

Any advice would be much appreciated!

Stephen Jones
Carlson School of Management
University of Minnesota
321 19th Ave S, Suite 4-169
Minneapolis, MN 55455
801-318-8243 (cell)
612-625-7805 (office)



On Mon, Sep 24, 2012 at 11:11 AM, Giulia Dotti Sani <
giulia.dottisani@gmail.com> wrote:

> I posted the same  question a few months ago, have a look here:
>
> https://stat.ethz.ch/pipermail/r-sig-mixed-models/2012q1/018070.html
>
> and the following threads.
> Hope it helps,
>
> Giulia Dotti Sani,
> University of Trento
> Italy
>
> On Fri, Sep 21, 2012 at 11:36 PM, Stephen Jones <jone2093@umn.edu> wrote:
> > Hello,
> >
> > I am using lme4 to analyze a dataset that has crossed random effects.
> There
> > are three outcomes of interest, and currently I am using three separate
> > linear mixed-effects models. I would like to use seemingly unrelated
> > regression (SUR) to perform cross-equation tests on the fixed effects
> > parameters.
> >
> > Is there a way to use SUR with lme4? Are there any papers that can serve
> as
> > examples or documentation that may help?
> >
> > (This is my first time posting to the group, so please let me know if I
> > should be including other info in my post.)
> >
> > Stephen Jones
> > Carlson School of Management
> > University of Minnesota
> >
> >         [[alternative HTML version deleted]]
> >
> > _______________________________________________
> > R-sig-mixed-models@r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>
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>

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