Every fitlme-based report (lme_*, paper_*, phase_*, and the variations'
analyze.m) now shows, per effect: residual-DF p, Satterthwaite-DF p, and --
for the interaction -- an HONEST test from a per-animal random-SLOPE model
(day|rat), whose Satterthwaite DF collapses toward the animal count.
New: tdcs_random_slope_interaction.m (shared helper). Wired into tdcs_lme,
tdcs_paper_lme, tdcs_phase_lme, variation_analyze; SUMMARY.csv gains
interaction_p_satt / interaction_p_rs. Regenerated all results/, variations/,
matched-effort outputs.
Key point this surfaces: Satterthwaite ~= residual on the random-INTERCEPT
model (the slope's error is at session level), so it does NOT fix
pseudoreplication; the random-slope model does. Effect: full-range mergeA2
interaction 0.009 -> 0.75 (collapses); unmerge_d0_5 0.015 -> 0.13 (n.s.);
the pooled-control early windows survive honestly (naive_a2_d0_5 0.001 ->
0.028; naive_boxa_d0_5 0.003 -> 0.036). Suite 42/42.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Add make_variations.m + variation_analyze.m generating 20 self-contained
subfolders under analysis/matlab/variations/, one per grouping x day-window,
each with exactly three files: data.csv (curated subset), analyze.m (a simple
standalone script fitting behavior ~ stim + day + stim:day + (1|rat) on the
success COUNT), and result.txt (its output). Plus variations/SUMMARY.csv.
Groupings (stim=1 / stim=0, other groups dropped):
unmerge B2 vs A2
right_only B2+Right vs A2 (Box-A dropped)
naive_a2 B2 vs A2+Naive (Right, Box-A dropped)
naive_boxa B2 vs A2+Naive+Box-A (Right dropped)
Windows: 0-10, 0-13, 0-5, 6-10, 6-13. All 20 have equal day coverage.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Experiments DB Dev