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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_10/result.txt
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==============================================================================
VARIATION: naive_a2_d0_10
VARIATION: naive_a2_d0_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(100)= 1.54 F(1)= 2.382 p=0.1259 p=0.1261 (df=95)
day (learning) t(100)= 15.09 F(1)=227.710 p=1.598e-27 p=4.059e-27 (df=96)
stim (main, window start) t(100)= 1.48 F(1)= 2.192 p=0.1418 p=0.1543 (df=20)
interaction 95% CI: [-0.41, +3.28]
interaction 95% CI: [-0.4093, +3.277]
HONEST LME (per-animal random slope, day|rat): interaction F(1,9.0)=1.16, p=0.3093
(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=0.1259, slope diff=+1.43)
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=0.1259, slope diff=+1.434)
Paper (N=24, count): interaction t(227)=2.68, F(1)=7.12, p=0.008.