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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>
This commit is contained in:
Experiments DB Dev
2026-07-23 14:37:50 -04:00
parent bb5e2d88c0
commit 378ad6da05
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analysis/matlab/variations/unmerge_d0_13/logpower_result.txt
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==============================================================================
LOG-DAY MODEL + COHEN'S f + POWER -- unmerge_d0_13
==============================================================================
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=3, control n=3 nrep=120, alpha=0.05
--- fitted on real data ---
stim x log(day) interaction: F(1,66)=8.712 p(resid)=0.004373 p(Satt)=0.004357 (df=67)
honest per-animal random slope (log-day): F(1,12.9)=6.96 p=0.02062
Cohen's f (interaction, partial eta^2=0.015) = 0.124 (small-medium; f: .10 small, .25 medium, .40 large)
--- power simulation (log-day ground truth: stim:logday=+11.06, ratSD=5.68, resSD=11.36) ---
true stim:log(day) = +11.06 (100% of observed)
N/group | per-animal power | LME power
------------------------------------------
3 | 0.53 | 0.91 <- observed
5 | 0.99 | 1.00
8 | 1.00 | 1.00
12 | 1.00 | 1.00
16 | 1.00 | 1.00
24 | 1.00 | 1.00
true stim:log(day) = +5.53 (50% of observed)
N/group | per-animal power | LME power
------------------------------------------
3 | 0.18 | 0.38 <- observed
5 | 0.41 | 0.54
8 | 0.78 | 0.80
12 | 0.86 | 0.91
16 | 0.97 | 0.98
24 | 0.98 | 0.98
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.