[Eeglablist] statistics in EEGLAB

Thu Nov 12 22:56:39 PST 2009

Dear all,

Recently I worked with a statistical analysis method called Linear Mixed
Models (LMM). This is relatively new to me so I hope I would not say
something wrong but here is my suggestion.

Why not including the subjects as a factor in the statistical analysis?
The problem is that the subjects at hand do not represent the entire
population of subjects. The nice thing is that this is exactly what LMM
can handle through the use of random effects. However I guess that the
statistical analysis will always reject the null hypothesis that the
dependent variable is the same for all subjects, leading to difficult
interpretation of the results. Anyway that might be a starting point to
answer your question. Any comments ?

In the case LMM are not familiar to you:

http://faculty.chass.ncsu.edu/garson/PA765/multilevel.htm

Hoping this can help,

best regards,

Guillaume Chanel

From: eeglablist-bounces at sccn.ucsd.edu
[mailto:eeglablist-bounces at sccn.ucsd.edu] On Behalf Of Arnaud Delorme
Sent: 11. marraskuuta 2009 23:10
To: Robert Brown
Cc: eeglablist
Subject: Re: [Eeglablist] statistics in EEGLAB

Dear Bob,

thanks for the comments. I think you are using the statmode option
"trial" from the command line. This option is quite experimental. It was
implemented a while ago and is probably not forward compatible with more
recent changes. Also, the "statmode", "trials" option (assuming it was
working) should only be used to plot a single subjects. The reason is
based on the type of null hypothesis.

When testing with 'statmode', 'subject' for two conditions, the NULL
hypothesis is: given the subjects I have recorded and given that these
subjects are a good representation of the general population of all
possible subjects, there is no difference between the
ERP/spectrum/ERSP/ITC between the two experimental conditions in the
general subject population. Using parametric, permutation, or bootstrap
statistics (and assumptions) you may either accept or reject this
hypothesis at a given confidence level.

When testing with 'statmode', 'trial' on a single subject (still two
conditions), the NULL hypothesis is : given the trials I have recorded
and given that these trials are a good representation of all the
population of trials for this subject, there is no difference between
the ERP/spectrum/ERSP/ITC between the two experimental conditions for
this subject. Again, using parametric, permutation, or bootstrap
statistics (and assumptions) you may either accept or reject this
hypothesis at a given confidence level.

As you can see the two hypothesis are quite different. One makes an
inference about the population of subjects and the other one about the
population of trials.

Now if you pool the trials from different subjects and attempt to
perform statistics, this is going to be more complex. The new hypothesis
would then be: given the trials I have recorded from my subjects and
given that these trials are a good representation of all the population
of trials from the general population of subjects, there is no
difference between the ERP/spectrum/ERSP/ITC between the two
experimental conditions in the general population of subjects. But the
hypothesis is relatively biased because I personally think that all the
trials are not a good representation of all the population of trials
from the general population of subjects. The trials are a good
representation of all the trials from all the subjects being presently
recorded but not necessarily of the general subject population.
Therefore the real NULL hypothesis would be : given the trials I have
recorded from all of my subjects and given that these trials are a good
representation of all the population of trials from these subjects,
there is no difference between the ERP/spectrum/ERSP/ITC between the two
experimental conditions in the recorded subjects. As you see, rejecting
the NULL this is relatively limited as we care about the general
population of subjects and not the recorded subjects.

If anybody has some better ideas (or Matlab function) of how to handle
the subject/trial problem (because it would be nice to include trials in
statistical analysis in order to make them more powerful), we will take
them.

Best,

Arno

ps: we will remove the 'statmode', 'trial' option for now.

pps: for basic inferential statistics, you may also refer to this book
chapter http://sccn.ucsd.edu/~arno/mypapers/statistics.pdf

On Nov 11, 2009, at 12:29 AM, Robert Brown wrote:

Dear Arno & others,

this does not seem to be as simple as Arno suggested (but thanks),

1. I have precomputed the values of these channels (with "savetrials",
"on")
2. these channels all have data
3. I can plot the data of the same channels when I use "statmode",
"subjects"
4. I'm using EEGLAB v7.1.3.13b 
5. I now tried it with v7.1.7.18b and I still get the log of zero error
(you guys might be interested that in addition I now get, in case of
permutations and bootstrap, "??? Error using ==> reshape" in
statcond>surrogate at 438 and statcond at 301 and with this latest
version the reshape error even happens with the "statmode", "subjects")

thus any other suggestions of what could be happening with my single
trial analysis in study would be very much appreciated.

thank you very much and take care,
Bob

2009/11/11 Arnaud Delorme <arno at ucsd.edu>

Dear Bob,

I think this might be because you are trying to plot ERSP of a channel
that contains only 0. This error was also arising in old versions of
EEGLAB when masking for significance.

Hope this helps,

Arno

On Nov 7, 2009, at 11:38 AM, Robert Brown wrote:

	Hi guys,

	I've been trying to get the study ersp analysis working on
single trials but I've not succeeded.

	in the function "std_readdata" I get the "Warning: Log of zero."
error, which is on the line ersp{c,g} = 20*log10(abs(ersp{c,g}));
meaning that the absolute value at some point is 0.
	(This leads to) further errors:

	??? Error using ==> set
	Bad value for axes property: 'CLim'
	Values must be increasing and non-NaN.

	Error in ==> caxis at 80
	           set(ax,'CLim',arg);

	Error in ==> tftopo at 714
	caxis([g.limits(5:6)]);

	I've tried to fix it but I'm not clever enough. any help would
be appreciated.

	thank you so much,,

	Bob <ATT00001.txt>

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