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experiments-database/analysis/matlab/variations/prev_f_full/logpower_result_rate.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 -- prev_f_full [metric: success RATE]
==============================================================================
model: behavior ~ stim + log(day) + stim:log(day) + (1|rat) (behavior = success RATE)
log(day) uses 1-indexed training day (our day 0 = paper "Day 1")
observed groups: stim n=12, control n=12 nrep=120, alpha=0.05
--- fitted on real data ---
stim x log(day) interaction: F(1,227)=2.888 p(resid)=0.0906 p(Satt)=0.09072 (df=208)
honest per-animal random slope (log-day): F(1,23.7)=2.05 p=0.1655
Cohen's f (interaction, partial eta^2=0.006) = 0.079 (small; f: .10 small, .25 medium, .40 large)
--- power simulation (log-day ground truth: stim:logday=+0.02595, ratSD=0.06838, resSD=0.08017) ---
true stim:log(day) = +0.02595 (100% of observed)
N/group | per-animal power | LME power
------------------------------------------
3 | 0.06 | 0.07
5 | 0.17 | 0.18
8 | 0.33 | 0.38
12 | 0.38 | 0.47 <- observed
16 | 0.55 | 0.62
24 | 0.64 | 0.60
true stim:log(day) = +0.01298 (50% of observed)
N/group | per-animal power | LME power
------------------------------------------
3 | 0.04 | 0.04
5 | 0.07 | 0.11
8 | 0.10 | 0.12
12 | 0.17 | 0.17 <- observed
16 | 0.10 | 0.15
24 | 0.15 | 0.17
Read per-animal as the honest power; LME matches the paper's power code (optimistic).