Experiments DB Dev
e1af1af7f4
Add make_boxa_variations.m producing 6 variation folders (data.csv + analyze.m + result.txt) for the paper LME over windows 0-5, 6-10, 0-10: boxa_a2 B2 vs A2 + Box-A (b2 vs a2+a) boxa_b2 B2 + Box-A vs A2 (b2+a vs a2) plus variations/boxa_summary.csv (residual / Satterthwaite / random-slope interaction p). Early window (0-5) is obs-level significant (res p~0.03-0.04) but n.s. under the honest random-slope test (rs p~0.13); later windows n.s. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
69 lines
2.9 KiB
Plaintext
69 lines
2.9 KiB
Plaintext
==============================================================================
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VARIATION: boxa_a2_d0_5
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==============================================================================
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model: behavior ~ stim + day + stim:day + (1|rat) (behavior = success COUNT)
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day = training day within window (0 = first analyzed day)
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treatment (stim=1): Electrode-Box-B2
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control (stim=0): Electrode-Box-A, Electrode-Box-A2
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N = 7 rats, 42 sessions raw day coverage: treat 0..5, control 0..5
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(equal day coverage over this window)
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==============================================================================
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FULL MODEL SUMMARY -- fitlme
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==============================================================================
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Linear mixed-effects model fit by ML
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Model information:
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Number of observations 42
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Fixed effects coefficients 4
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Random effects coefficients 7
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Covariance parameters 2
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Formula:
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behavior ~ 1 + day*stim + (1 | rat)
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Model fit statistics:
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AIC BIC LogLikelihood Deviance
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339.96 350.39 -163.98 327.96
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Fixed effects coefficients (95% CIs):
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Name Estimate SE tStat DF pValue
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{'(Intercept)'} 10.06 4.3445 2.3155 38 0.026083
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{'day' } 10.543 1.4349 7.3472 38 8.3775e-09
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{'stim' } -0.55159 6.6363 -0.083116 38 0.9342
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{'day:stim' } 4.6762 2.1919 2.1334 38 0.03941
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Lower Upper
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1.2645 18.855
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7.638 13.448
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-13.986 12.883
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0.2389 9.1135
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Random effects covariance parameters (95% CIs):
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Group: rat (7 Levels)
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Name1 Name2 Type Estimate
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{'(Intercept)'} {'(Intercept)'} {'std'} 0
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Lower Upper
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NaN NaN
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Group: Error
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Name Estimate Lower Upper
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{'Res Std'} 12.006 9.6941 14.868
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effect t(df) / F(df1) p (resid) Satterthwaite: p (df)
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----------------------------------------------------------------------------
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stim x day (interaction) t(38)= 2.13 F(1)= 4.551 p=0.03941 p=0.03878 (df=42)
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day (learning) t(38)= 7.35 F(1)= 53.982 p=8.377e-09 p=4.651e-09 (df=42)
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stim (main, window start) t(38)= -0.08 F(1)= 0.007 p=0.9342 p=0.9342 (df=42)
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interaction 95% CI: [+0.24, +9.11]
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HONEST LME (per-animal random slope, day|rat): interaction F(1,7.0)=2.87, p=0.1341
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(Satterthwaite DF ~= residual on this random-intercept model; the random-slope
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model above is the honest learning-rate test -- DF collapses toward the animal count.)
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INTERPRETATION: stim x day interaction SIGNIFICANT positive -- treatment improves FASTER (benefit accumulates) (p=0.03941, slope diff=+4.68)
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Paper (N=24): interaction t(227)=2.68, F(1)=7.12, p=0.008.
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