docs(matlab): label tDCS main effect as Day 1 (= our day 0), matching the paper

The model already evaluates the tDCS main effect at day 0, which is the paper's
'Day 1'; relabel the report/docstring to state the equivalence explicitly so the
'equal on Day 1' comparison is unambiguous. No model change (re-indexing day
would move the main-effect evaluation point off Day 1). Suite 31/31.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

analysis/matlab/tdcs_lme.m

@@ -8,8 +8,11 @@ function L = tdcs_lme(S, cfg)
 %
 %   replicating the published formulation (a linear mixed-effects model for the
 %   number of successful reaches with a days x tDCS interaction, a main effect
-%   of days, and a main effect of tDCS). `day` is used raw (not centered), so
+%   of days, and a main effect of tDCS). `day` is raw and 0-indexed, and OUR
-%   the tDCS main effect is the group difference on the first day ("Day 1").
+%   day 0 corresponds to the paper's "Day 1", so the tDCS main effect is the
+%   group difference on Day 1 -- directly comparable to the paper's "equal on
+%   Day 1" test. (Do not re-index day to 1-based: that would move the main
+%   effect's evaluation point off Day 1.)
 %
 %   L fields:
 %     .lme         the LinearMixedModel object

analysis/matlab/tdcs_lme_report.m

@@ -11,14 +11,15 @@ s = [s sprintf('LINEAR MIXED MODEL (days x tDCS) -- scenario: %s\n', scenario)];
 s = [s sprintf('%s\n', bar)];
 s = [s sprintf('model: success ~ day * tDCS + (1|subject)   [tDCS: %s = 1 vs %s = 0]\n', ...
     cfg.anchorHigh, cfg.anchorLow)];
-s = [s sprintf('N = %d subjects, %d sessions   (day used raw: tDCS main = first-day difference)\n\n', ...
+s = [s sprintf('N = %d subjects, %d sessions\n', L.nSubjects, L.nObs)];
-    L.nSubjects, L.nObs)];
+s = [s sprintf('(day is raw and 0-indexed: our day 0 = the paper''s "Day 1", so the tDCS\n')];
+s = [s sprintf(' main effect below is the group difference on Day 1 -- comparable to the paper.)\n\n')];
 
 s = [s sprintf('%-27s %-14s %-13s %s\n', 'effect', 't (df)', 'F (df1)', 'p')];
 s = [s sprintf('%s\n', repmat('-', 1, 70))];
 s = [s localRow('days x tDCS (interaction)', L.interaction)];
 s = [s localRow('days (learning)', L.day)];
-s = [s localRow('tDCS (main, at day 0)', L.tDCS)];
+s = [s localRow('tDCS (main, at Day 1)', L.tDCS)];
 
 s = [s sprintf('\nINTERPRETATION\n')];
 if L.interaction.p >= 0.05
@@ -32,9 +33,9 @@ s = [s sprintf('  - days x tDCS interaction: %s (p=%.4f, slope diff=%.2f) -> %s.
     localSig(L.interaction.p), L.interaction.p, L.interaction.estimate, interTxt)];
 s = [s sprintf('  - days (learning): %s (p=%.2g) -> performance improves with training.\n', ...
     localSig(L.day.p), L.day.p)];
-s = [s sprintf('  - tDCS main effect at day 0: %s (p=%.4f) -> the groups %s on the first day.\n', ...
+s = [s sprintf('  - tDCS main effect on Day 1 (our day 0): %s (p=%.4f) -> the groups %s on Day 1.\n', ...
     localSig(L.tDCS.p), L.tDCS.p, ...
-    localPick(L.tDCS.p < 0.05, 'already DIFFER', 'are comparable'))];
+    localPick(L.tDCS.p < 0.05, 'already DIFFER', 'are comparable (as in the paper)'))];
 
 s = [s sprintf('\nPaper reference (N=24): interaction t(227)=2.68, F(1)=7.12, p=0.008;\n')];
 s = [s sprintf('  days t(227)=9.64, F(1)=267.64, p=1.2e-18; tDCS t(227)=0.23, F(1)=0.053, p=0.81.\n')];