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experiments-database/analysis/matlab/variations/naive_a2_d6_10/logpower_result.txt
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Experiments DB Dev 6ba21a1a35 analysis(matlab): rate + count outputs, variation batch 2
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_a2_d6_10 [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=6 nrep=120, alpha=0.05
--- fitted on real data ---
stim x log(day) interaction: F(1,41)=0.662 p(resid)=0.4205 p(Satt)=0.4211 (df=36)
honest per-animal random slope (log-day): F(1,9.0)=0.46 p=0.5139
Cohen's f (interaction, partial eta^2=0.006) = 0.076 (small; f: .10 small, .25 medium, .40 large)
--- power simulation (log-day ground truth: stim:logday=-16.93, ratSD=10.99, resSD=10.51) ---
true stim:log(day) = -16.93 (100% of observed)
N/group | per-animal power | LME power
------------------------------------------
3 | 0.07 | 0.12 <- observed
5 | 0.07 | 0.07
8 | 0.20 | 0.27
12 | 0.30 | 0.34
16 | 0.34 | 0.36
24 | 0.51 | 0.53
true stim:log(day) = -8.464 (50% of observed)
N/group | per-animal power | LME power
------------------------------------------
3 | 0.03 | 0.07 <- observed
5 | 0.07 | 0.07
8 | 0.08 | 0.11
12 | 0.07 | 0.08
16 | 0.11 | 0.12
24 | 0.13 | 0.14
Read per-animal as the honest power; LME matches the paper's power code (optimistic).