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

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
parent 6ba21a1a35
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VARIATION: naive_boxa_d0_13 [metric: success RATE (success/attempts)]
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model: behavior ~ stim + day + stim:day + (1|rat) (behavior = success RATE (success/attempts))
day = training day within window (0 = first analyzed day)
treatment (stim=1): Electrode-Box-B2
control (stim=0): Electrode-Box-A, Electrode-Box-A2, Naive
N = 11 rats, 136 sessions raw day coverage: treat 0..13, control 0..13
(equal day coverage over this window)
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FULL MODEL SUMMARY -- fitlme
==============================================================================
Linear mixed-effects model fit by ML
Model information:
Number of observations 136
Fixed effects coefficients 4
Random effects coefficients 11
Covariance parameters 2
Formula:
behavior ~ 1 + day*stim + (1 | rat)
Model fit statistics:
AIC BIC LogLikelihood Deviance
-202.35 -184.87 107.17 -214.35
Fixed effects coefficients (95% CIs):
Name Estimate SE tStat DF pValue
{'(Intercept)'} 0.22695 0.026364 8.6084 132 1.9298e-14
{'day' } 0.034099 0.0028279 12.058 132 4.9136e-23
{'stim' } 0.061777 0.049323 1.2525 132 0.2126
{'day:stim' } 0.009461 0.0052125 1.8151 132 0.071786
Lower Upper
0.1748 0.2791
0.028506 0.039693
-0.035788 0.15934
-0.00084987 0.019772
Random effects covariance parameters (95% CIs):
Group: rat (11 Levels)
Name1 Name2 Type Estimate
{'(Intercept)'} {'(Intercept)'} {'std'} 0.047732
Lower Upper
0.026198 0.086966
Group: Error
Name Estimate Lower Upper
{'Res Std'} 0.10455 0.092342 0.11837
effect t(df) / F(df1) p (resid) Satterthwaite: p (df)
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stim x day (interaction) t(132)= 1.82 F(1)= 3.294 p=0.07179 p=0.07185 (df=128)
day (learning) t(132)= 12.06 F(1)=145.397 p=4.914e-23 p=5.237e-23 (df=131)
stim (main, window start) t(132)= 1.25 F(1)= 1.569 p=0.2126 p=0.2207 (df=28)
interaction 95% CI: [-0.0008499, +0.01977]
HONEST LME (per-animal random slope, day|rat): interaction F(1,10.0)=2.86, p=0.1216
(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=0.07179, slope diff=+0.009461)
Paper (N=24, count): interaction t(227)=2.68, F(1)=7.12, p=0.008.