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experiments-database/analysis/matlab/variations/boxa_a2_d6_10/logpower_result.txt
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Experiments DB Dev 0a438a4649 analysis(matlab): rate + count outputs, variation batch 1
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-07-24 02:32:51 -04:00

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LOG-DAY MODEL + COHEN'S f + POWER -- boxa_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=3 nrep=120, alpha=0.05
--- fitted on real data ---
stim x log(day) interaction: F(1,26)=0.252 p(resid)=0.6199 p(Satt)=0.6202 (df=24)
honest per-animal random slope (log-day): F(1,6.0)=0.19 p=0.6783
Cohen's f (interaction, partial eta^2=0.004) = 0.065 (small; f: .10 small, .25 medium, .40 large)
--- power simulation (log-day ground truth: stim:logday=+9.522, ratSD=6.321, resSD=8.298) ---
true stim:log(day) = +9.522 (100% of observed)
N/group | per-animal power | LME power
------------------------------------------
3 | 0.02 | 0.06 <- observed
5 | 0.09 | 0.13
8 | 0.12 | 0.12
12 | 0.11 | 0.17
16 | 0.14 | 0.16
24 | 0.32 | 0.34
true stim:log(day) = +4.761 (50% of observed)
N/group | per-animal power | LME power
------------------------------------------
3 | 0.06 | 0.10 <- observed
5 | 0.07 | 0.07
8 | 0.05 | 0.07
12 | 0.09 | 0.10
16 | 0.09 | 0.12
24 | 0.12 | 0.15
Read per-animal as the honest power; LME matches the paper's power code (optimistic).