feat(matlab): add Satterthwaite DF + honest random-slope test to LME reports

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>
This commit is contained in:
Experiments DB Dev
2026-07-22 15:45:19 -04:00
parent 5fcd97f81a
commit 8a18c894dd
77 changed files with 2066 additions and 345 deletions
@@ -56,13 +56,18 @@ Group: Error
effect t (df) F (df1) p
------------------------------------------------------------------
stim x day (interaction) t(134)= 2.66 F(1)= 7.068 p=0.008801
day (learning) t(134)= 15.01 F(1)= 225.182 p=1.766e-30
stim (main, Day 1) t(134)= 1.28 F(1)= 1.629 p=0.204
effect t(df) / F(df1) p (resid) Satterthwaite: p (df)
----------------------------------------------------------------------------
stim x day (interaction) t(134)= 2.66 F(1)= 7.068 p=0.008801 p=0.008831 (df=130)
day (learning) t(134)= 15.01 F(1)=225.182 p=1.766e-30 p=2.418e-30 (df=132)
stim (main, Day 1) t(134)= 1.28 F(1)= 1.629 p=0.204 p=0.2142 (df=24)
interaction 95% CI: [+0.46, +3.14]
HONEST LME -- per-rat random slope (day|rat): interaction F(1,54.8)=6.46, p=0.01387
Satterthwaite DF on the random-INTERCEPT model above stays ~= residual (the
slope's error is at session level), so it does NOT fix pseudoreplication. A per-animal
random slope collapses the interaction DF toward the animal count -- the honest test.
INTERPRETATION
- stim x day interaction: SIGNIFICANT (p=0.0088, slope diff=+1.80) -> tDCS (Box-B2) improves FASTER -- benefit accumulates over training.
- stim main effect on Day 1 (our day 0): n.s. (p=0.2040) -> groups are comparable on Day 1.