==============================================================================
VARIATION: naive_a2_d0_13   [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-B2
control   (stim=0): Electrode-Box-A2, Naive
N = 10 rats, 124 sessions   raw day coverage: treat 0..13, control 0..13
(equal day coverage over this window)

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

Linear mixed-effects model fit by ML

Model information:
    Number of observations             124
    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
    1055.4    1072.3    -521.69          1043.4  

Fixed effects coefficients (95% CIs):
    Name                   Estimate    SE         tStat     DF     pValue    
    {'(Intercept)'}        16.252       4.4327    3.6664    120    0.00036779
    {'day'        }        6.4053      0.43948    14.575    120    2.5469e-28
    {'stim'       }         11.52        8.023    1.4359    120       0.15363
    {'day:stim'   }        1.6137      0.77637    2.0785    120      0.039797


    Lower       Upper 
      7.4757    25.029
      5.5352    7.2755
     -4.3648    27.405
    0.076509    3.1508

Random effects covariance parameters (95% CIs):
Group: rat (10 Levels)
    Name1                  Name2                  Type           Estimate
    {'(Intercept)'}        {'(Intercept)'}        {'std'}        8.4599  


    Lower     Upper 
    4.8243    14.835

Group: Error
    Name               Estimate    Lower     Upper 
    {'Res Std'}        15.264      13.405    17.381


effect                     t(df) / F(df1)     p (resid)    Satterthwaite: p (df)
----------------------------------------------------------------------------
stim x day (interaction)   t(120)=  2.08 F(1)=  4.320  p=0.0398    p=0.03986 (df=117)
day (learning)             t(120)= 14.57 F(1)=212.424  p=2.547e-28    p=3.246e-28 (df=119)
stim (main, window start)  t(120)=  1.44 F(1)=  2.062  p=0.1536    p=0.1655 (df=21)
interaction 95% CI: [+0.07651, +3.151]
HONEST LME (per-animal random slope, day|rat): interaction F(1,41.7)=3.81, p=0.05781
  (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=0.0398, slope diff=+1.614)
Paper (N=24, count): interaction t(227)=2.68, F(1)=7.12, p=0.008.
