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experiments-database/analysis/matlab/variations/naive_boxa_d0_10/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_d0_10 [metric: # successes (count)]
==============================================================================
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=8 nrep=120, alpha=0.05
--- fitted on real data ---
stim x log(day) interaction: F(1,111)=3.705 p(resid)=0.05681 p(Satt)=0.05696 (df=105)
honest per-animal random slope (log-day): F(1,8.2)=2.03 p=0.1913
Cohen's f (interaction, partial eta^2=0.007) = 0.086 (small; f: .10 small, .25 medium, .40 large)
--- power simulation (log-day ground truth: stim:logday=+8.428, ratSD=8.126, resSD=14.95) ---
true stim:log(day) = +8.428 (100% of observed)
N/group | per-animal power | LME power
------------------------------------------
3 | 0.17 | 0.35 <- observed
5 | 0.44 | 0.56
8 | 0.68 | 0.69 <- observed
12 | 0.91 | 0.92
16 | 0.95 | 0.96
24 | 0.99 | 1.00
true stim:log(day) = +4.214 (50% of observed)
N/group | per-animal power | LME power
------------------------------------------
3 | 0.07 | 0.07 <- observed
5 | 0.08 | 0.14
8 | 0.23 | 0.29 <- observed
12 | 0.28 | 0.28
16 | 0.55 | 0.53
24 | 0.63 | 0.62
Read per-animal as the honest power; LME matches the paper's power code (optimistic).