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confidence.m
function confidence(dprime)
% confidence.m
if ~exist('dprime'),
dprime=1;
end;
signal_trials=spm_invNcdf(rand(1,100),dprime,1);
noise_trials=spm_invNcdf(rand(1,100),0,1);
lambda=[-0.5 0.0 0.4 0.9];
confratings=zeros(100,2); % 100 trials X signal/noise
% create trial data
for st=1:100,
% find all threshold levels that are above the current datapoint
conf=find(signal_trials(st)=c);
if ~isempty(tmp),
p(c,sn)=max(size(tmp))/max(size(confratings));
end;
end;
end;
p
plot(p(:,2),p(:,1),'r*-')
axis([0 1 0 1]);
hold on
plot([0 1],[0 1],'b')
hold off
2009 Advanced Neuroimaging Summer School: July 20-31, 2009
