============================================================================== VARIATION: naive_a2_d0_10 ============================================================================== model: behavior ~ stim + day + stim:day + (1|rat) (behavior = success COUNT) day = training day within window (0 = first analyzed day) treatment (stim=1): Electrode-Box-B2 control (stim=0): Electrode-Box-A2, Naive N = 10 rats, 104 sessions raw day coverage: treat 0..10, control 0..10 (equal day coverage over this window) ============================================================================== FULL MODEL SUMMARY -- fitlme ============================================================================== Linear mixed-effects model fit by ML Model information: Number of observations 104 Fixed effects coefficients 4 Random effects coefficients 10 Covariance parameters 2 Formula: behavior ~ 1 + day*stim + (1 | rat) Model fit statistics: AIC BIC LogLikelihood Deviance 869.17 885.04 -428.58 857.17 Fixed effects coefficients (95% CIs): Name Estimate SE tStat DF pValue {'(Intercept)'} 10.33 4.4952 2.298 100 0.023646 {'day' } 8.0905 0.53615 15.09 100 1.598e-27 {'stim' } 12.019 8.117 1.4807 100 0.14184 {'day:stim' } 1.4337 0.92893 1.5434 100 0.12589 Lower Upper 1.4115 19.248 7.0268 9.1542 -4.0853 28.123 -0.40926 3.2767 Random effects covariance parameters (95% CIs): Group: rat (10 Levels) Name1 Name2 Type Estimate {'(Intercept)'} {'(Intercept)'} {'std'} 8.753 Lower Upper 5.0208 15.26 Group: Error Name Estimate Lower Upper {'Res Std'} 13.78 11.942 15.902 effect t (df) F (df1) p ------------------------------------------------------------------ stim x day (interaction) t(100)= 1.54 F(1)= 2.382 p=0.1259 day (learning) t(100)= 15.09 F(1)= 227.710 p=1.598e-27 stim (main, window start) t(100)= 1.48 F(1)= 2.192 p=0.1418 interaction 95% CI: [-0.41, +3.28] 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.