[R-sig-ME] multicolinearity?

[ONKELINX, Thierry]

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 at 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 at r-project.org 
> [mailto:r-sig-mixed-models-bounces at r-project.org] Namens Lucas Kid
> Verzonden: maandag 29 november 2010 16:27
> Aan: r-sig-mixed-models at 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
> 
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