function P = tdcs_phase_lme(mergeKey, cfg, phases)
%TDCS_PHASE_LME Refit the days x tDCS LME within learning phases (Box-B2 vs A2).
%   P = TDCS_PHASE_LME(MERGEKEY, CFG) fits the same linear mixed model as the
%   lme_* scenarios -- success ~ dayp*tDCS + (1|subject) -- SEPARATELY within
%   each learning phase, for the Box-B2 (tDCS=1) vs Box-A2 (tDCS=0) subset of
%   the MERGEKEY grouping ('unmerged' | 'mergeA2' | 'mergeB2'). `dayp` is `day`
%   centered at each phase's start, so the tDCS main effect reads as the group
%   difference on the phase's first day (the interaction and slopes are
%   invariant to this centering). Prints a per-phase table and writes
%   results/phase_<MERGEKEY>.txt.
%
%   P = TDCS_PHASE_LME(MERGEKEY, CFG, PHASES) uses custom phase windows
%   (default {[0 5],[6 10],[6 13]}), each a [loDay hiDay] pair.
%
%   P.phases{k} has: .phase .nSub .a2Slope .b2Slope .dayP (learning) .tDCSlevelP
%   (between-group level at phase start) .interP .interEst .interCI (the
%   between-group learning-rate difference and its 95% CI).

if nargin < 3 || isempty(phases)
    phases = {[0 5], [6 10], [6 13]};
end

Sfull = tdcs_scenario_data([mergeKey '_full']);
T = Sfull(ismember(Sfull.group, {cfg.anchorLow, cfg.anchorHigh}), :);

P = struct('mergeKey', mergeKey, 'phases', {cell(1, numel(phases))});

bar = repmat('=', 1, 78);
s = sprintf('%s\n', bar);
s = [s sprintf('PHASED days x tDCS LME -- %s (Box-B2 vs Box-A2)\n', mergeKey)];
s = [s sprintf('%s\n', bar)];
s = [s sprintf('model per phase: success ~ dayp*tDCS + (1|subject)  [dayp = day - phaseStart]\n\n')];
s = [s sprintf('%-9s N  A2slope B2slope  day p     tDCS(lvl) p  interaction p  slopeDiff [95%% CI]\n', 'phase')];
s = [s sprintf('%s\n', repmat('-', 1, 92))];

for k = 1:numel(phases)
    ph = phases{k};
    Tp = T(T.day >= ph(1) & T.day <= ph(2), :);
    Tp.dayp = Tp.day - ph(1);
    Tp.tDCS = double(Tp.group == cfg.anchorHigh);

    lme = fitlme(Tp, 'success ~ dayp*tDCS + (1|subject)');
    C = lme.Coefficients; A = anova(lme); ci = coefCI(lme);
    ii = strcmp(C.Name, 'dayp:tDCS');
    di = strcmp(C.Name, 'dayp');

    e = struct();
    e.phase = ph;
    e.nSub = numel(unique(Tp.subject));
    e.a2Slope = C.Estimate(di);
    e.b2Slope = C.Estimate(di) + C.Estimate(ii);
    e.dayP = A.pValue(strcmp(A.Term, 'dayp'));
    e.tDCSlevelP = A.pValue(strcmp(A.Term, 'tDCS'));
    e.interP = A.pValue(strcmp(A.Term, 'dayp:tDCS'));
    e.interEst = C.Estimate(ii);
    e.interCI = ci(ii, :);
    P.phases{k} = e;

    s = [s sprintf('%d-%-6d %d  %6.2f  %6.2f  %-9.2g %-11.3f  %-13.3f %+.2f [%+.2f, %+.2f]\n', ...
        ph(1), ph(2), e.nSub, e.a2Slope, e.b2Slope, e.dayP, e.tDCSlevelP, ...
        e.interP, e.interEst, e.interCI(1), e.interCI(2))]; %#ok<AGROW>
end

s = [s sprintf(['\nNote: the interaction p (and CI) use fitlme observation-level DF and are\n' ...
    'ANTICONSERVATIVE at these small subject counts (see tdcs_power_sim). The early\n' ...
    'phase carries the Box-B2 faster-acquisition signal; late phases converge.\n'])];

fprintf('%s', s);
localWrite(['phase_' mergeKey], s);

end

function localWrite(name, s)
thisDir = fileparts(mfilename('fullpath'));
resDir = fullfile(thisDir, 'results');
if ~exist(resDir, 'dir'); mkdir(resDir); end
fid = fopen(fullfile(resDir, [name '.txt']), 'w');
if fid < 0; error('tdcs_phase_lme:fopen', 'Cannot open results file for "%s".', name); end
cleanup = onCleanup(@() fclose(fid)); %#ok<NASGU>
fprintf(fid, '%s', s);
end