The design is a repeated measures with 3 instances.  There are 3 groups:
 Controls, Heavy Cocaine Users, Light Cocaine Users.

I reshaped the data so that there was one variable for the 3 instances
called AvgTrials.  Time is the indicator of each instance.

Here is the model call:

mod5 <- lme(AvgTrials ~ time + factor(group_id) + time*factor(group_id),
random = ~ 1 | group_id, data = tmp.dat, method = "ML", na.action = na.omit)

What else would you need here?

-Edward


On Mon, Sep 6, 2010 at 8:52 AM, ONKELINX, Thierry
<Thierry.ONKELINX@inbo.be>wrote:

> Dear Edward,
>
> You have no degrees of freedom left to estimate those p-values. Your
> design does not allows for the model your implemented. We need a brief
> summary of your design in order to help you further.
>
> HTH,
>
> 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-help-bounces@r-project.org
> > [mailto:r-help-bounces@r-project.org] Namens Edward Patzelt
> > Verzonden: maandag 6 september 2010 15:43
> > Aan: r-help@r-project.org
> > Onderwerp: [R] nlme Output
> >
> > Everyone -
> >
> > What do the NaN's mean here?  Is this analysis a problem?
> >
> >
> > Linear mixed-effects model fit by maximum likelihood
> >  Data: tmp.dat
> >        AIC      BIC    logLik
> >   1611.251 1638.363 -797.6253
> >
> > Random effects:
> >  Formula: ~1 | group_id
> >          (Intercept) Residual
> > StdDev: 0.0003077668 9.236715
> >
> > Fixed effects: AvgTrials ~ time + factor(group_id) + time *
> > factor(group_id)
> >                            Value Std.Error  DF   t-value p-value
> > (Intercept)            18.159722  3.576664 213  5.077279  0.0000
> > time                    4.192708  1.655674 213  2.532327  0.0121
> > factor(group_id)2      -6.929563  5.235700   0 -1.323522     NaN
> > factor(group_id)3      -1.654554  4.189575   0 -0.394922     NaN
> > time:factor(group_id)2  1.729911  2.423658 213  0.713760  0.4762
> > time:factor(group_id)3 -2.555111  1.939396 213 -1.317478  0.1891
> >  Correlation:
> >                        (Intr) time   fc(_)2 fc(_)3 t:(_)2
> > time                   -0.926
> > factor(group_id)2      -0.683  0.632
> > factor(group_id)3      -0.854  0.790  0.583
> > time:factor(group_id)2  0.632 -0.683 -0.926 -0.540
> > time:factor(group_id)3  0.790 -0.854 -0.540 -0.926  0.583
> >
> > Standardized Within-Group Residuals:
> >        Min         Q1        Med         Q3        Max
> > -1.8842754 -0.6979785 -0.3370998  0.5666704  3.0943948
> >
> > Number of Observations: 219
> > Number of Groups: 3
> > Warning message:
> > In pt(q, df, lower.tail, log.p) : NaNs produced
> >
> >       [[alternative HTML version deleted]]
> >
> > ______________________________________________
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> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide
> > http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> >
>
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-- 
Edward H. Patzelt
Research Assistant – TRiCAM Lab
University of Minnesota – Psychology/Psychiatry
VA Medical Center
Office: N437 Elliot Hall - Twin Cities Campus
Phone: 612-624-3892  Email: patze003@umn.edu

Please consider the environment before printing this email
www.psych.umn.edu/research/tricam

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