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experiments-database/analysis/matlab/variations/unmerge_d0_10/logpower_result.txt
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Experiments DB Dev 1606eb698b analysis(matlab): rate + count outputs, variation batch 4
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-07-24 02:32:53 -04:00

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LOG-DAY MODEL + COHEN'S f + POWER -- unmerge_d0_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(1,57)=6.230 p(resid)=0.01548 p(Satt)=0.01528 (df=61)
honest per-animal random slope (log-day): F(1,15.0)=5.28 p=0.0363
Cohen's f (interaction, partial eta^2=0.017) = 0.131 (small-medium; f: .10 small, .25 medium, .40 large)
--- power simulation (log-day ground truth: stim:logday=+11.6, ratSD=0, resSD=12.93) ---
true stim:log(day) = +11.6 (100% of observed)
N/group | per-animal power | LME power
------------------------------------------
3 | 0.34 | 0.69 <- observed
5 | 0.82 | 0.92
8 | 0.97 | 0.97
12 | 1.00 | 1.00
16 | 1.00 | 1.00
24 | 1.00 | 1.00
true stim:log(day) = +5.801 (50% of observed)
N/group | per-animal power | LME power
------------------------------------------
3 | 0.10 | 0.25 <- observed
5 | 0.26 | 0.40
8 | 0.53 | 0.58
12 | 0.61 | 0.72
16 | 0.90 | 0.90
24 | 0.97 | 0.97
Read per-animal as the honest power; LME matches the paper's power code (optimistic).