Experiments DB Dev
378ad6da05
Add variation_logpower.m (self-contained) + make_variation_logpower.m, dropping logpowersim.m + logpower_result.txt into all 28 variation folders. Matches the paper's power code: models behavior ~ stim + log(day) + stim:log(day) + (1|rat) (log(day+1), since our day 0 = paper Day 1), reports Cohen's f (partial eta^2 of the interaction) and the interaction under residual/Satterthwaite/honest random-slope DF, then runs the Monte-Carlo power sim on the log-day ground truth (per-animal cluster-honest + LME power). Notable: under log(day) the accumulating divergence is captured more sharply, so several full-window scenarios reach honest significance that were n.s. under raw day (e.g. right_only_d0_13 honest p=0.003, unmerge_d0_13 0.021, unmerge_d0_10 0.036); Cohen's f is small-medium (~0.10-0.34). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
37 lines
1.7 KiB
Plaintext
37 lines
1.7 KiB
Plaintext
==============================================================================
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LOG-DAY MODEL + COHEN'S f + POWER -- unmerge_d0_5
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==============================================================================
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model: behavior ~ stim + log(day) + stim:log(day) + (1|rat) (success COUNT)
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log(day) uses 1-indexed training day (our day 0 = paper "Day 1")
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observed groups: stim n=3, control n=3 nrep=120, alpha=0.05
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--- fitted on real data ---
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stim x log(day) interaction: F(1,32)=4.849 p(resid)=0.03498 p(Satt)=0.03414 (df=36)
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honest per-animal random slope (log-day): F(1,7.2)=3.65 p=0.09636
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Cohen's f (interaction, partial eta^2=0.039) = 0.200 (small-medium; f: .10 small, .25 medium, .40 large)
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--- power simulation (log-day ground truth: stim:logday=+16.48, ratSD=0.00, resSD=13.58) ---
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true stim:log(day) = +16.48 (100% of observed)
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N/group | per-animal power | LME power
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------------------------------------------
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3 | 0.33 | 0.64 <- observed
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5 | 0.66 | 0.78
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8 | 0.93 | 0.97
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12 | 0.99 | 1.00
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16 | 1.00 | 1.00
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24 | 1.00 | 1.00
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true stim:log(day) = +8.24 (50% of observed)
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N/group | per-animal power | LME power
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------------------------------------------
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3 | 0.09 | 0.24 <- observed
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5 | 0.21 | 0.29
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8 | 0.28 | 0.38
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12 | 0.47 | 0.59
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16 | 0.69 | 0.69
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24 | 0.90 | 0.92
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Read the per-animal column as the honest power; the LME column matches the
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paper's power code (anova interaction p, observation-level DF) and is optimistic.
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