Thanks, Thierry, but I still receive the same error, albeit with fewer nan's
in my verbose parameter output:

> (m1 <- glmer(Correct ~ Months * ( Stimulus + Focus) + (1|Subject),
family=binomial, data=mydataset, verbose=TRUE))
  0:           nan: 0.0774439 -2.86253 0.309665  1.18527  2.32723  1.68874
 2.42588  3.43032 -1.68977  2.91237      nan -0.169244 -0.232590 -0.212932
-0.261447 -0.345893 0.0672266 -0.269589      nan
Error in asMethod(object) : matrix is not symmetric [1,2]
In addition: Warning message:
In mer_finalize(ans) : gr cannot be computed at initial par (65)

vs

> (m1 <- glmer(Correct ~ Months * Stimulus * Focus + (1|Subject),
family=binomial, data=mydataset, verbose=TRUE))
  0:           nan: 0.0774439 -2.86253 0.309665  1.18527  2.32723  1.68874
 2.42588  3.43032 -1.68977  2.91237      nan -0.169244 -0.232590 -0.212932
-0.261447 -0.345893 0.0672266 -0.269589      nan      nan      nan      nan
     nan      nan      nan      nan      nan      nan      nan      nan
 nan      nan      nan
Error in asMethod(object) : matrix is not symmetric [1,2]
In addition: Warning message:
In mer_finalize(ans) : gr cannot be computed at initial par (65)

Thanks,

Luke

On Mon, Nov 29, 2010 at 11:09 AM, ONKELINX, Thierry <
Thierry.ONKELINX@inbo.be> wrote:

> Dear Lucas,
>
> It will be probably sufficient to drop the Focus:Stimulus interaction.
>
> m1f <- glmer(Correct ~ Months*(Focus + Stimulus) + (1|Subject),
> family=binomial, data=mydataset)
>
> You will be some NA values because stimulus is nested in focus.
>
> Best regards,
>
> Thierry
>
> ------------------------------------------------------------------------
> ----
> ir. Thierry Onkelinx
> Instituut voor natuur- en bosonderzoek
> team Biometrie & Kwaliteitszorg
> Gaverstraat 4
> 9500 Geraardsbergen
> Belgium
>
> Research Institute for Nature and Forest
> team Biometrics & Quality Assurance
> Gaverstraat 4
> 9500 Geraardsbergen
> Belgium
>
> tel. + 32 54/436 185
> Thierry.Onkelinx@inbo.be
> www.inbo.be
>
> To call in the statistician after the experiment is done may be no more
> than asking him to perform a post-mortem examination: he may be able to
> say what the experiment died of.
> ~ Sir Ronald Aylmer Fisher
>
> The plural of anecdote is not data.
> ~ Roger Brinner
>
> The combination of some data and an aching desire for an answer does not
> ensure that a reasonable answer can be extracted from a given body of
> data.
> ~ John Tukey
>
>
> > -----Oorspronkelijk bericht-----
> > Van: r-sig-mixed-models-bounces@r-project.org
> > [mailto:r-sig-mixed-models-bounces@r-project.org] Namens Lucas Kid
> > Verzonden: maandag 29 november 2010 16:27
> > Aan: r-sig-mixed-models@r-project.org
> > Onderwerp: [R-sig-ME] multicolinearity?
> >
> > Mixed modelers,
> >
> > I have a dataset (mydataset) where subjects' (Subject)
> > responses (Correct) to a stimulus (Stimulus) was tested over
> > time (Months). There were 8 stimuli, 2 of which had focus A
> > and 6 had focus B (Focus).  At each time point, subjects were
> > tested multiple times for each stimuli.  Subject, Stimulus,
> > and Focus are all factors.
> >
> > I have run model as follows:
> >
> > (m1 <- glmer(Correct ~ Months*Stimulus + (1|Subject), family=binomial,
> > data=mydataset))
> > (m2 <- glmer(Correct ~ Months*Stimulus + (1|Subject) + (0 + Months
> > |Subject), family=binomial, data=mydataset))
> > (m3 <- glmer(Correct ~ Months*Stimulus + (1 + Months
> > |Subject), family=binomial, data=mydataset))
> > (m4 <- glmer(Correct ~ Months*Stimulus + (1 + Months +
> > Stimulus |Subject), family=binomial, data=mydataset))
> > (m5 <- glmer(Correct ~ Months*Stimulus + (1 + Months +
> > Stimulus + Months * Stimulus |Subject), family=binomial,
> > data=mydataset))
> >
> > I would like to test Focus to see if, when controlling for
> > Focus, the effect of Stimulus goes away.
> >
> > (m1f <- glmer(Correct ~ Months*Stimulus*Focus + (1|Subject),
> > family=binomial, data=mydataset))
> >
> > However, I get the following error:
> >
> > Error in asMethod(object) : matrix is not symmetric [1,2] In
> > addition: Warning message:
> > In mer_finalize(ans) : gr cannot be computed at initial par (65)
> >
> > I believe this is a case of multicolinearity between Focus
> > and Stimulus.
> > Would that be a correct assumption?  What options do I have
> > in order to examine the relationship between Correct and
> > Stimulus/Focus in a mixed-effects situation.
> >
> > I'm using version 0.999375-35 of lme4.
> >
> > Thanks!
> >
> > Luke
> >
> >       [[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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