Confidence Interval for the negative effect

[sclab-shuo]

I suspect this error from the observation of a counterintuitive output for a simple mediation analysis with these 3 vectors as X, M, and Y variables. There is a significant negative effect after BCa correction of path c; however, the CI output always spans from negative to slightly positive number (e.g. -0.0213 to 0.0034). Please see the attached output saved from the "stats" variable.

I narrow this issue to the code from this script “bootbca_ci.m”. I understand this script works well for the positive effect, but maybe with a negative effect, the ci_upper and ci_lower should switched to obtain the asymmetric confidence interval before BCa manipulation.

a1 = z_0 + ( (z_0 + zalpha1) ./ (1 - a .* (z_0 + zalpha1)) );
p1 = normcdf(a1);

a2 = z_0 + ( (z_0 + zalpha2) ./ (1 - a .* (z_0 + zalpha2)) );
p2 = normcdf(a2);

ci_lower = prctile(bstat, 100 .* p1);
ci_upper = prctile(bstat, 100 .* p2);

% SC added: ------
ci_lower_n = prctile(bstat, 100 .* (1.-p2));
ci_upper_n = prctile(bstat, 100 .* (1.-p1));

testvalue = 0;
% prctile of the distribution below nullvalue (2-tailed)
% pct = min( [sum(bstat < testvalue); sum(bstat > testvalue)] ) ./ B;
pct_lowertail = sum(bstat < testvalue) ./ B;
pct_uppertail = sum(bstat > testvalue) ./ B;

% lower tail is smaller for positive effect. is_lowertail == 1 effects
% should be positive.
is_lowertail = pct_lowertail < pct_uppertail;

ci = [ci_lower ci_upper];

clear ci
for i=1:size(ci_lower, 1)
if is_lowertail(i) == 1
ci(i,1) = ci_lower(i,i);
ci(i,2) = ci_upper(i,i);
else
ci(i,1) = ci_lower_n(i,i);
ci(i,2) = ci_upper_n(i,i);
end
end

example data input and output file
https://drive.google.com/file/d/1X2iIecCE2WjQpyh2bqz3QmlmjsnT3i-0/view?usp=sharing