Thanks very much for that reply. The subjects are all 16 years old, right
handed, equally split across sex etc, its a very homogenous group. The time
effects are not significant because, due to a bunch of factors I won't go
into, the time order of the measurements is randomised within each subject.
ie you can't equate any order within one subject to the order of measurement
within another subject. There is no data on whether the alpha frequency - or
any aspect of the EEG - is generated by a single constant process or not.
For example, an electrode at the scalp records the spatial average of
activity from a large, 10 cm^2, area of cortex. As well, there is a temporal
window, say 2-seconds, within which analysis occurs. Many spatially and
temporally independent processes within that area can appear as one process
within the spatial and temporal window - basic experimental limitation. One
of my research questions is to examine the reliability of EEG to see if that
gives us a handle on the number and stationarity of the processes generating
the signal. Error introduced by the measuring apparatus is random and
consistent across all frequencies. Therefore alterations in reliability are
mostly due to nonstationarity in the generators. The reason for using
reliability, rather than some other measure of stationarity, is that the end
point - hopefully - is a small group of variables for which we can find the
genetic locii. It looks as though the peak Alpha frequency and its amplitude
qualify, they have the highest reliability with the least amount of data.
Thankyou again for your time
Greg Hooper
Donald F. Burrill <[EMAIL PROTECTED]> wrote in message
[EMAIL PROTECTED]">news:[EMAIL PROTECTED]...
> On Sun, 26 Dec 1999, Greg Hooper wrote:
>
> > I want to use a one-way random effects anova intraclass correlation on
> > the following data. 70 subjects, each with 30 measurements of the one
> > property - their EEG alpha frequency - taken across a 5 minute interval.
>
> Every ten seconds, then? How are you proposing to model the time
> dependency(ies) across the 5 minutes? Is it reasonable to model EEG
> alpha as constant during that time? One would suppose not, since you
> write of "a one-way random effects anova" and the random effects in
> question are, presumably, time effects? But then it would appear that
> you would be considering the 70 first measurements (one for each subject)
> as somehow equivalent, and possibly systematically (if randomly)
> different from the 70 second measurements, and the 70 third measurements,
> and so on. That doesn't sound to me any more reasonable than a constant
> over the 5 minutes. But perhaps I misapprehend your purpose...
> Presumably the 70 subjects are homogeneous with respect to possible
> between-subject variables of interest (sex or age, e.g.), else you'd have
> mentioned the design factors...
>
> > I'm looking at both single and average measures for reliability.
> > When assessing normality of the distribution ...
>
> You must mean "assessing non-normality"?
>
> > do I look at the entire data set, i.e. 70*30 measures, or do I look at
> > the single columns of alpha, i.e. 30 distributions of 70 measures each.
>
> By "alpha" I take it you mean the EEG alpha frequency measures, not the
> reliability coefficient alpha. In general, the assumption associated
> with anova is that the residuals -- i.e., the departures from the model
> one is trying to fit -- be normally distributed. In practice, it usually
> suffices if they're unimodal and not too asymmetric. It follows that you
> cannot assess possible non-normality of residuals until after you have
> attempted to fit a model.
>
> > Is the within subject distribution important, i.e. 70 distributions of
> > 30 measures each?
>
> It certainly would have some bearing, one would expect, on how you chose
> to model the time series. If your model were too simple for the universe
> of discourse, the distributions of residuals -- and perhaps particularly
> the time-dependent distribution of residuals -- would provide some
> evidence that the model needed revision.
>
> > Thank you for your time, I understand this is trivial but I find the
> > statistic texts i have consulted quite opaque on this point.
>
> Not all that trivial (in the corrupt modern sense; might well be trivial
> as a metaphor for the classical sense of "belonging to the trivium", i.e.
> the first three of the seven liberal arts). And textbooks do tend to be
> opaque, I'm afraid.
> -- DFB.
> ------------------------------------------------------------------------
> Donald F. Burrill [EMAIL PROTECTED]
> 348 Hyde Hall, Plymouth State College, [EMAIL PROTECTED]
> MSC #29, Plymouth, NH 03264 603-535-2597
> 184 Nashua Road, Bedford, NH 03110 603-471-7128
>
