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experiments-database/analysis/matlab/variations/naive_boxa_d6_13/logpower_result.txt
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Experiments DB Dev 0e16690c8f analysis(matlab): rate + count outputs, variation batch 3
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-07-24 02:32:52 -04:00

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LOG-DAY MODEL + COHEN'S f + POWER -- naive_boxa_d6_13 [metric: # successes (count)]
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model: behavior ~ stim + log(day) + stim:log(day) + (1|rat) (behavior = # successes (count))
log(day) uses 1-indexed training day (our day 0 = paper "Day 1")
observed groups: stim n=3, control n=7 nrep=120, alpha=0.05
--- fitted on real data ---
stim x log(day) interaction: F(1,69)=0.239 p(resid)=0.6263 p(Satt)=0.6264 (df=65)
honest per-animal random slope (log-day): F(1,9.1)=0.07 p=0.8013
Cohen's f (interaction, partial eta^2=0.001) = 0.034 (small; f: .10 small, .25 medium, .40 large)
--- power simulation (log-day ground truth: stim:logday=+6.701, ratSD=10.78, resSD=11.38) ---
true stim:log(day) = +6.701 (100% of observed)
N/group | per-animal power | LME power
------------------------------------------
3 | 0.05 | 0.07 <- observed
5 | 0.13 | 0.15
8 | 0.11 | 0.17
12 | 0.15 | 0.12
16 | 0.23 | 0.25
24 | 0.23 | 0.24
true stim:log(day) = +3.35 (50% of observed)
N/group | per-animal power | LME power
------------------------------------------
3 | 0.05 | 0.08 <- observed
5 | 0.04 | 0.07
8 | 0.06 | 0.10
12 | 0.05 | 0.05
16 | 0.06 | 0.07
24 | 0.12 | 0.11
Read per-animal as the honest power; LME matches the paper's power code (optimistic).