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analysis(matlab): rate + count outputs, variation batch 2

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Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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Experiments DB Dev
2026-07-24 02:32:52 -04:00
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analysis/matlab/variations/naive_a2_d0_13/result.txt
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==============================================================================
VARIATION: naive_a2_d0_13
VARIATION: naive_a2_d0_13 [metric: success COUNT]
==============================================================================
model: behavior ~ stim + day + stim:day + (1|rat) (behavior = success COUNT)
day = training day within window (0 = first analyzed day)
@@ -60,9 +60,9 @@ effect t(df) / F(df1) p (resid) Satterthwaite: p (df)
stim x day (interaction) t(120)= 2.08 F(1)= 4.320 p=0.0398 p=0.03986 (df=117)
day (learning) t(120)= 14.57 F(1)=212.424 p=2.547e-28 p=3.246e-28 (df=119)
stim (main, window start) t(120)= 1.44 F(1)= 2.062 p=0.1536 p=0.1655 (df=21)
interaction 95% CI: [+0.08, +3.15]
interaction 95% CI: [+0.07651, +3.151]
HONEST LME (per-animal random slope, day|rat): interaction F(1,41.7)=3.81, p=0.05781
(Satterthwaite DF ~= residual on this random-intercept model; the random-slope
model above is the honest learning-rate test -- DF collapses toward the animal count.)
INTERPRETATION: stim x day interaction SIGNIFICANT positive -- treatment improves FASTER (benefit accumulates) (p=0.0398, slope diff=+1.61)
Paper (N=24): interaction t(227)=2.68, F(1)=7.12, p=0.008.
INTERPRETATION: stim x day interaction SIGNIFICANT positive -- treatment improves FASTER (benefit accumulates) (p=0.0398, slope diff=+1.614)
Paper (N=24, count): interaction t(227)=2.68, F(1)=7.12, p=0.008.