[Eeglablist] statcond/statcondfieldtrip cluster correction
Taylor Hearn
thearn at asu.edu
Wed Apr 24 11:55:46 PDT 2019
Hi Arno,
Thank you for this clarification! I still seem to be having some issues
with statcondfieldtrip though. Perhaps you could look at my syntax and
provide some feedback? Here is what I'm in inputting to statcondfieldtrip:
cfg.method = 'template';
cfg.template =
'C:\Users\thearn\Documents\MATLAB\fieldtrip-20180423\template\neighbours\elec1020_neighb.mat';
cfg.channel = chan;
cfg.correctm = 'cluster';
[neighbours, cfg] = ft_prepare_neighbours(cfg);
[mmn_stats, ~, ~] = statcondfieldtrip(...
data,...
'paired', 'on',...
'method', 'permutation',...
'naccu', 1000,...
'alpha', 0.05,...
'neighbours', neighbours,...
'structoutput', 'on');
"data" is a 2x1 cell array, each cell containing a matrix with dimensions:
samples X channels X subjects
This yields the following output:
Trying to load sensor neighbours from a template
Successfully loaded neighbour structure from
C:\Users\thearn\Documents\MATLAB\fieldtrip-20180423\template\neighbours\elec1020_neighb.mat
there are on average 7.6 neighbours per channel
the call to "ft_prepare_neighbours" took 0 seconds
1 x 2, paired data, computing T values
Warning: could not determine dimord of "freq" in:
dimord: 'rpt_chan_freq_time'
powspctrm: [8×151×9 double]
label: {9×1 cell}
freq: 1
time: 1
Warning: could not determine dimord of "powspctrm" in:
dimord: 'rpt_chan_freq_time'
powspctrm: [8×151×9 double]
label: {9×1 cell}
freq: 1
time: 1
the call to "ft_selectdata" took 0 seconds
Warning: could not determine dimord of "powspctrm" in:
powspctrm: [8×151×9 double]
label: {9×1 cell}
freq: 1
time: 1
dimord: 'rpt_chan_freq_time'
cfg: {[] []}
using "ft_statistics_montecarlo" for the statistical testing
Warning: The field cfg.neighbours is unused, it will be removed from your
configuration
using "ft_statfun_depsamplesT" for the single-sample statistics
constructing randomized design
total number of measurements = 2
total number of variables = 16
number of independent variables = 1
number of unit variables = 1
number of within-cell variables = 0
number of control variables = 0
using a permutation resampling approach
repeated measurement in variable 2 over 2 levels
number of repeated measurements in each level is 1 1
Error using ft_statfun_depsamplesT (line 79)
Invalid specification of the design array.
Error in ft_statistics_montecarlo (line 272)
[statobs, cfg] = statfun(cfg, dat, design);
Error in ft_freqstatistics (line 190)
[stat, cfg] = statmethod(cfg, dat, design);
I've tried to trace the source of the error in the code, but I can't seem
to find the source of the "Invalid specification of the design array". Any
thoughts?
Thanks again,
Taylor
Taylor Hearn
Biomedical Engineering PhD Candidate
APAcT-IGERT Fellow
Arizona State University
On Wed, Apr 24, 2019 at 1:04 AM Arnaud Delorme <arno at ucsd.edu> wrote:
> Hi Taylor,
>
> It is better to use statcondfieldtrip, which calls uses the original
> cluster method. The ‘cluster’ option of statcond is an equivalent
> implementation although it cannot take channel neighbors into account. It
> only works for time or time x frequency decompositions. It was added
> because of frustration with the speed of the Fieldtrip original cluster
> method (although it is not much faster).
>
> Best wishes,
>
> Arno
>
> > On Apr 17, 2019, at 8:14 AM, Taylor Hearn <thearn at asu.edu> wrote:
> >
> > Hi,
> >
> > I would like to perform a cluster correction for multiple comparisons,
> but
> > I am a little confused by the syntax of these two functions. Given my
> > within group comparison for my data (samples X channels X subjects), is
> it
> > correct to assume that this should be set up as a 2x1 cell? Also, I know
> I
> > want to use the following options:
> >
> > paired = on
> > method = permuation
> > naccu = 1000
> > alpha = 0.05
> >
> > but from here I am not sure if I should use the "cluster" option for
> > "statcond" or the "neighbours" option for "statcondfieldtrip". If I use
> > "neighbours" could you also detail the input to the
> "ft_prepare_neighbours"
> > functions?
> >
> > Thanks in advance,
> > Taylor
> >
> > Taylor Hearn
> > Biomedical Engineering PhD Candidate
> > APAcT-IGERT Fellow
> > Arizona State University
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