77b631bcac
Adds cfg.mergeNaive and scenario/paper/phase/power support. This pooled grouping is the closest replication of the paper's full pattern: paper LME interaction F(1)=7.30, p=0.008 (paper 7.12/0.008), stim main n.s. (p=0.21 = equal on Day 1), strong day effect; the overall tDCS advantage is significant at the cluster-honest per-animal level (rate p=0.003) and well powered. Adds a grouping test. Suite 38/38. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
22 lines
1.0 KiB
Matlab
22 lines
1.0 KiB
Matlab
%RUN_ALL Run all tDCS scenarios and write results/<scenario>.txt for each.
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% Usage: matlab -batch "run_all"
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% Covers the 6 GLMM scenarios and their 6 linear "days x tDCS" (lme_*) variants.
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scenarios = {'unmerged_full', 'unmerged_d0_10', ...
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'mergeA2_full', 'mergeA2_d0_10', ...
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'mergeB2_full', 'mergeB2_d0_10', ...
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'lme_unmerged_full', 'lme_unmerged_d0_10', ...
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'lme_mergeA2_full', 'lme_mergeA2_d0_10', ...
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'lme_mergeB2_full', 'lme_mergeB2_d0_10', ...
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'lme_unmerged_d0_13', 'lme_mergeA2_d0_13', 'lme_mergeB2_d0_13', ...
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'phase_unmerged', 'phase_mergeA2', 'phase_mergeB2', ...
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'paper_unmerged', 'paper_mergeA2', 'paper_mergeB2', ...
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'mergeNaive_full', 'paper_mergeNaive', 'phase_mergeNaive'};
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for i = 1:numel(scenarios)
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fprintf('\n\n### Running scenario: %s ###\n', scenarios{i});
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tdcs_glm(scenarios{i});
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end
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fprintf('\n\nAll %d scenarios complete. See analysis/matlab/results/*.txt.\n', numel(scenarios));
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