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analysis(matlab): add log(day) model + Cohen's f + power to every variation

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Add variation_logpower.m (self-contained) + make_variation_logpower.m,
dropping logpowersim.m + logpower_result.txt into all 28 variation folders.
Matches the paper's power code: models behavior ~ stim + log(day) +
stim:log(day) + (1|rat) (log(day+1), since our day 0 = paper Day 1), reports
Cohen's f (partial eta^2 of the interaction) and the interaction under
residual/Satterthwaite/honest random-slope DF, then runs the Monte-Carlo power
sim on the log-day ground truth (per-animal cluster-honest + LME power).

Notable: under log(day) the accumulating divergence is captured more sharply,
so several full-window scenarios reach honest significance that were n.s. under
raw day (e.g. right_only_d0_13 honest p=0.003, unmerge_d0_13 0.021,
unmerge_d0_10 0.036); Cohen's f is small-medium (~0.10-0.34).

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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Experiments DB Dev
2026-07-23 14:37:50 -04:00
parent bb5e2d88c0
commit 378ad6da05
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analysis/matlab/variations/boxa_b2_d0_5/logpower_result.txt
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==============================================================================
LOG-DAY MODEL + COHEN'S f + POWER -- boxa_b2_d0_5
==============================================================================
model: behavior ~ stim + log(day) + stim:log(day) + (1|rat) (success COUNT)
log(day) uses 1-indexed training day (our day 0 = paper "Day 1")
observed groups: stim n=4, control n=3 nrep=120, alpha=0.05
--- fitted on real data ---
stim x log(day) interaction: F(1,38)=3.165 p(resid)=0.08322 p(Satt)=0.08246 (df=42)
honest per-animal random slope (log-day): F(1,9.4)=2.59 p=0.1407
Cohen's f (interaction, partial eta^2=0.026) = 0.163 (small-medium; f: .10 small, .25 medium, .40 large)
--- power simulation (log-day ground truth: stim:logday=+13.68, ratSD=0.00, resSD=14.91) ---
true stim:log(day) = +13.68 (100% of observed)
N/group | per-animal power | LME power
------------------------------------------
3 | 0.18 | 0.42 <- observed
5 | 0.43 | 0.59
8 | 0.68 | 0.75
12 | 0.81 | 0.88
16 | 0.96 | 0.97
24 | 0.98 | 0.99
true stim:log(day) = +6.84 (50% of observed)
N/group | per-animal power | LME power
------------------------------------------
3 | 0.07 | 0.14 <- observed
5 | 0.12 | 0.19
8 | 0.17 | 0.19
12 | 0.31 | 0.39
16 | 0.43 | 0.49
24 | 0.70 | 0.75
Read the per-animal column as the honest power; the LME column matches the
paper's power code (anova interaction p, observation-level DF) and is optimistic.