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analysis(matlab): rate + count outputs, variation batch 3

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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/prev_f_full/result.txt
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==============================================================================
VARIATION: prev_f_full
VARIATION: prev_f_full [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(227)= 2.66 F(1)= 7.088 p=0.008315 p=0.008365 (df=208)
day (learning) t(227)= 8.94 F(1)= 79.838 p=1.43e-16 p=2.16e-16 (df=209)
stim (main, window start) t(227)= 0.92 F(1)= 0.839 p=0.3606 p=0.3656 (df=37)
interaction 95% CI: [+0.15, +0.97]
interaction 95% CI: [+0.1456, +0.9749]
HONEST LME (per-animal random slope, day|rat): interaction F(1,24.0)=3.01, p=0.09541
(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=0.008315, slope diff=+0.56)
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=0.008315, slope diff=+0.5602)
Paper (N=24, count): interaction t(227)=2.68, F(1)=7.12, p=0.008.