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experiments-database/analysis/matlab/variations/right_only_d6_13/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 -- right_only_d6_13 [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=4, control n=2 nrep=120, alpha=0.05
--- fitted on real data ---
stim x log(day) interaction: F(1,38)=5.774 p(resid)=0.02125 p(Satt)=0.02133 (df=37)
honest per-animal random slope (log-day): F(1,0.0)=3.19 p=NaN
Cohen's f (interaction, partial eta^2=0.036) = 0.194 (small-medium; f: .10 small, .25 medium, .40 large)
--- power simulation (log-day ground truth: stim:logday=+28.42, ratSD=6.482, resSD=7.389) ---
true stim:log(day) = +28.42 (100% of observed)
N/group | per-animal power | LME power
------------------------------------------
3 | 0.57 | 0.86
5 | 0.93 | 0.98
8 | 1.00 | 1.00
12 | 1.00 | 1.00
16 | 1.00 | 1.00
24 | 1.00 | 1.00
true stim:log(day) = +14.21 (50% of observed)
N/group | per-animal power | LME power
------------------------------------------
3 | 0.17 | 0.30
5 | 0.37 | 0.55
8 | 0.62 | 0.68
12 | 0.81 | 0.85
16 | 0.90 | 0.92
24 | 1.00 | 1.00
Read per-animal as the honest power; LME matches the paper's power code (optimistic).