==============================================================================
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 (resid)    Satterthwaite: p (df)
----------------------------------------------------------------------------
stim x day (interaction)   t(69)=  0.63 F(1)=  0.397  p=0.5308    p=0.5309 (df=65)
day (learning)             t(69)=  4.26 F(1)= 18.109  p=6.446e-05    p=6.931e-05 (df=64)
stim (main, window start)  t(69)=  2.21 F(1)=  4.886  p=0.03039    p=0.0412 (df=17)
interaction 95% CI: [-1.89, +3.64]
HONEST LME (per-animal random slope, day|rat): interaction F(1,8.5)=0.16, p=0.6966
  (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=0.5308, slope diff=+0.87)
Paper (N=24): interaction t(227)=2.68, F(1)=7.12, p=0.008.