============================================================================== VARIATION: naive_a2_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-A2, Naive N = 9 rats, 65 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 65 Fixed effects coefficients 4 Random effects coefficients 9 Covariance parameters 2 Formula: behavior ~ 1 + day*stim + (1 | rat) Model fit statistics: AIC BIC LogLikelihood Deviance 535.5 548.54 -261.75 523.5 Fixed effects coefficients (95% CIs): Name Estimate SE tStat DF pValue {'(Intercept)'} 66.813 5.1278 13.03 61 2.7998e-19 {'day' } 2.8262 0.83395 3.3889 61 0.0012345 {'stim' } 21.913 8.8928 2.4641 61 0.016568 {'day:stim' } 1.1553 1.4855 0.77769 61 0.43976 Lower Upper 56.56 77.067 1.1586 4.4937 4.1309 39.695 -1.8152 4.1258 Random effects covariance parameters (95% CIs): Group: rat (9 Levels) Name1 Name2 Type Estimate {'(Intercept)'} {'(Intercept)'} {'std'} 9.7589 Lower Upper 5.6191 16.948 Group: Error Name Estimate Lower Upper {'Res Std'} 12.033 10.004 14.473 effect t (df) F (df1) p ------------------------------------------------------------------ stim x day (interaction) t(61)= 0.78 F(1)= 0.605 p=0.4398 day (learning) t(61)= 3.39 F(1)= 11.485 p=0.001235 stim (main, window start) t(61)= 2.46 F(1)= 6.072 p=0.01657 interaction 95% CI: [-1.82, +4.13] INTERPRETATION: stim x day interaction n.s. -- slopes parallel (no differential learning rate) (p=0.4398, slope diff=+1.16) Paper (N=24): interaction t(227)=2.68, F(1)=7.12, p=0.008.