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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_d6_10/result.txt
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==============================================================================
VARIATION: naive_a2_d6_10
VARIATION: naive_a2_d6_10 [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(41)= -0.76 F(1)= 0.582 p=0.4499 p=0.4505 (df=36)
day (learning) t(41)= 4.38 F(1)= 19.183 p=8.027e-05 p=9.813e-05 (df=36)
stim (main, window start) t(41)= 2.73 F(1)= 7.453 p=0.00929 p=0.01541 (df=15)
interaction 95% CI: [-6.57, +2.97]
interaction 95% CI: [-6.565, +2.965]
HONEST LME (per-animal random slope, day|rat): interaction F(1,9.0)=0.44, p=0.5223
(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 n.s. -- slopes parallel (no differential learning rate) (p=0.4499, slope diff=-1.80)
Paper (N=24): interaction t(227)=2.68, F(1)=7.12, p=0.008.
INTERPRETATION: stim x day interaction n.s. -- slopes parallel (no differential learning rate) (p=0.4499, slope diff=-1.8)
Paper (N=24, count): interaction t(227)=2.68, F(1)=7.12, p=0.008.