==============================================================================
VARIATION: boxa_b2_d0_5   [metric: success COUNT]
==============================================================================
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-A, Electrode-Box-B2
control   (stim=0): Electrode-Box-A2
N = 7 rats, 42 sessions   raw day coverage: treat 0..5, control 0..5
(equal day coverage over this window)

==============================================================================
FULL MODEL SUMMARY -- fitlme
==============================================================================

Linear mixed-effects model fit by ML

Model information:
    Number of observations              42
    Fixed effects coefficients           4
    Random effects coefficients          7
    Covariance parameters                2

Formula:
    behavior ~ 1 + day*stim + (1 | rat)

Model fit statistics:
    AIC       BIC       LogLikelihood    Deviance
    341.62    352.04    -164.81          329.62  

Fixed effects coefficients (95% CIs):
    Name                   Estimate    SE        tStat       DF    pValue    
    {'(Intercept)'}         12.524     5.8127      2.1546    38      0.037599
    {'day'        }         9.8571     1.5596      6.3204    38    2.0711e-07
    {'stim'       }        -4.7262     7.6895    -0.61463    38       0.54246
    {'day:stim'   }         4.7071     2.0631      2.2816    38      0.028206


    Lower      Upper 
    0.75663    24.291
     6.6999    13.014
    -20.293     10.84
    0.53057    8.8837

Random effects covariance parameters (95% CIs):
Group: rat (7 Levels)
    Name1                  Name2                  Type           Estimate
    {'(Intercept)'}        {'(Intercept)'}        {'std'}        5.8715  


    Lower    Upper 
    2.486    13.868

Group: Error
    Name               Estimate    Lower     Upper 
    {'Res Std'}        11.3        8.9402    14.283


effect                     t(df) / F(df1)     p (resid)    Satterthwaite: p (df)
----------------------------------------------------------------------------
stim x day (interaction)   t(38)=  2.28 F(1)=  5.206  p=0.02821    p=0.02871 (df=35)
day (learning)             t(38)=  6.32 F(1)= 39.947  p=2.071e-07    p=2.928e-07 (df=35)
stim (main, window start)  t(38)= -0.61 F(1)=  0.378  p=0.5425    p=0.5456 (df=20)
interaction 95% CI: [+0.5306, +8.884]
HONEST LME (per-animal random slope, day|rat): interaction F(1,7.0)=2.92, p=0.131
  (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 SIGNIFICANT positive -- treatment improves FASTER (benefit accumulates) (p=0.02821, slope diff=+4.707)
Paper (N=24, count): interaction t(227)=2.68, F(1)=7.12, p=0.008.
