function [s, cfg] = ft_statfun_diff(cfg, dat, design)

% FT_STATFUN_DIFF demonstrates how to compute the difference of the mean in two

% conditions. Although it can be used for statistical testing, it will have rather

% limited sensitivity and is not really suited for inferential testing.

%

% This function serves as an example for a statfun. You can use such a function with

% the statistical framework in FieldTrip using FT_TIMELOCKSTATISTICS,

% FT_FREQSTATISTICS or FT_SOURCESTATISTICS to perform a statistical test, without

% having to worry about the representation of the data.

%

% Use this function by calling the high-level statistic functions as

% [stat] = ft_freqstatistics(cfg, freq1, freq2, ...)

% with the following configuration option:

% cfg.statistic = 'ft_statfun_diff_itc'

%

% The experimental design is specified as:

% cfg.ivar = independent variable, row number of the design that contains the labels of the conditions to be compared (default=1)

%

% The labels for the independent variable should be specified as the number 1 and 2.

%

% See also FT_TIMELOCKSTATISTICS, FT_FREQSTATISTICS or FT_SOURCESTATISTICS, and see FT_STATFUN_MEAN for a similar example

% Copyright (C) 2006, Robert Oostenveld

%

% This file is part of FieldTrip, see http://www.fieldtriptoolbox.org

% for the documentation and details.

%

% FieldTrip is free software: you can redistribute it and/or modify

% it under the terms of the GNU General Public License as published by

% the Free Software Foundation, either version 3 of the License, or

% (at your option) any later version.

%

% FieldTrip is distributed in the hope that it will be useful,

% but WITHOUT ANY WARRANTY; without even the implied warranty of

% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the

% GNU General Public License for more details.

%

% You should have received a copy of the GNU General Public License

% along with FieldTrip. If not, see <http://www.gnu.org/licenses/>.

%

% $Id$

% set the defaults

cfg.ivar = ft_getopt(cfg, 'ivar', 1);

sel1 = find(design(cfg.ivar,:)==1); % select replications that belong to condition 1

sel2 = find(design(cfg.ivar,:)==2); % select replications that belong to condition 2

n1 = length(sel1);

n2 = length(sel2);

if (n1+n2)<size(design, 2)

% there are apparently replications that belong neither to condition 1, nor to condition 2

ft_warning('inappropriate design, it should only contain 1''s and 2''s');

end

% compute the averages and the difference

avg1 = nanmean(dat(:,sel1), 2);

avg2 = nanmean(dat(:,sel2), 2);

% return the difference in the means as statistic of interest

s.stat = avg1 - avg2;