============================================================================== VARIATION: naive_boxa_d6_13 ============================================================================== 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-A, Electrode-Box-A2, Naive N = 10 rats, 73 sessions raw day coverage: treat 6..13, control 6..13 (equal day coverage over this window) ============================================================================== FULL MODEL SUMMARY -- fitlme ============================================================================== Linear mixed-effects model fit by ML Model information: Number of observations 73 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 595.91 609.65 -291.95 583.91 Fixed effects coefficients (95% CIs): Name Estimate SE tStat DF pValue {'(Intercept)'} 68.651 4.9672 13.821 69 1.4737e-21 {'day' } 3.1029 0.72917 4.2555 69 6.4463e-05 {'stim' } 20.083 9.0854 2.2105 69 0.030392 {'day:stim' } 0.87369 1.3869 0.62995 69 0.53081 Lower Upper 58.741 78.56 1.6483 4.5576 1.958 38.208 -1.8931 3.6405 Random effects covariance parameters (95% CIs): Group: rat (10 Levels) Name1 Name2 Type Estimate {'(Intercept)'} {'(Intercept)'} {'std'} 10.755 Lower Upper 6.51 17.768 Group: Error Name Estimate Lower Upper {'Res Std'} 11.525 9.6827 13.718 effect t (df) F (df1) p ------------------------------------------------------------------ stim x day (interaction) t(69)= 0.63 F(1)= 0.397 p=0.5308 day (learning) t(69)= 4.26 F(1)= 18.109 p=6.446e-05 stim (main, window start) t(69)= 2.21 F(1)= 4.886 p=0.03039 interaction 95% CI: [-1.89, +3.64] INTERPRETATION: stim x day interaction n.s. -- slopes parallel (no differential learning rate) (p=0.5308, slope diff=+0.87) Paper (N=24): interaction t(227)=2.68, F(1)=7.12, p=0.008.