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
2.8 KiB
Plaintext
69 lines
2.8 KiB
Plaintext
==============================================================================
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VARIATION: boxa_a2_d0_10
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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, 72 sessions raw day coverage: treat 0..10, control 0..10
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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 72
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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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590.8 604.46 -289.4 578.8
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Fixed effects coefficients (95% CIs):
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Name Estimate SE tStat DF pValue
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{'(Intercept)'} 15.599 3.8531 4.0485 68 0.00013444
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{'day' } 8.3258 0.69175 12.036 68 1.6397e-18
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{'stim' } 6.7494 5.8389 1.1559 68 0.25175
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{'day:stim' } 1.1985 1.0141 1.1818 68 0.2414
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Lower Upper
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7.9104 23.288
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6.9454 9.7061
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-4.9019 18.401
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-0.82514 3.2221
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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'} 13.471 11.441 15.861
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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(68)= 1.18 F(1)= 1.397 p=0.2414 p=0.2412 (df=72)
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day (learning) t(68)= 12.04 F(1)=144.862 p=1.64e-18 p=6.575e-19 (df=72)
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stim (main, window start) t(68)= 1.16 F(1)= 1.336 p=0.2517 p=0.2515 (df=72)
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interaction 95% CI: [-0.83, +3.22]
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HONEST LME (per-animal random slope, day|rat): interaction F(1,14.0)=0.68, p=0.4245
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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 n.s. -- slopes parallel (no differential learning rate) (p=0.2414, slope diff=+1.20)
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Paper (N=24): interaction t(227)=2.68, F(1)=7.12, p=0.008.
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