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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_5/result.txt
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==============================================================================
VARIATION: naive_a2_d0_5
VARIATION: naive_a2_d0_5 [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(55)= 3.45 F(1)= 11.924 p=0.001073 p=0.001152 (df=49)
day (learning) t(55)= 7.32 F(1)= 53.591 p=1.125e-09 p=2.092e-09 (df=49)
stim (main, window start) t(55)= 0.05 F(1)= 0.002 p=0.9606 p=0.9609 (df=20)
interaction 95% CI: [+2.92, +11.00]
interaction 95% CI: [+2.922, +11]
HONEST LME (per-animal random slope, day|rat): interaction F(1,9.7)=6.65, p=0.02815
(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=0.001073, slope diff=+6.96)
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=0.001073, slope diff=+6.962)
Paper (N=24, count): interaction t(227)=2.68, F(1)=7.12, p=0.008.