==============================================================================
VARIATION: naive_boxa_d6_13   [metric: success RATE (success/attempts)]
==============================================================================
model: behavior ~ stim + day + stim:day + (1|rat)   (behavior = success RATE (success/attempts))
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
    -143.92    -130.17    77.958           -155.92 

Fixed effects coefficients (95% CIs):
    Name                   Estimate     SE           tStat      DF    pValue    
    {'(Intercept)'}          0.50639     0.029658     17.074    69    1.7857e-26
    {'day'        }         0.013881    0.0046444     2.9887    69     0.0038784
    {'stim'       }          0.13179      0.05426     2.4289    69      0.017756
    {'day:stim'   }        0.0016506    0.0088296    0.18693    69       0.85226


    Lower        Upper   
      0.44722     0.56555
    0.0046157    0.023146
     0.023544     0.24004
    -0.015964    0.019265

Random effects covariance parameters (95% CIs):
Group: rat (10 Levels)
    Name1                  Name2                  Type           Estimate
    {'(Intercept)'}        {'(Intercept)'}        {'std'}        0.061972


    Lower       Upper  
    0.036939    0.10397

Group: Error
    Name               Estimate    Lower       Upper   
    {'Res Std'}        0.073458    0.061716    0.087434


effect                     t(df) / F(df1)     p (resid)    Satterthwaite: p (df)
----------------------------------------------------------------------------
stim x day (interaction)   t(69)=  0.19 F(1)=  0.035  p=0.8523    p=0.8523 (df=65)
day (learning)             t(69)=  2.99 F(1)=  8.933  p=0.003878    p=0.003964 (df=64)
stim (main, window start)  t(69)=  2.43 F(1)=  5.899  p=0.01776    p=0.02572 (df=18)
interaction 95% CI: [-0.01596, +0.01927]
HONEST LME (per-animal random slope, day|rat): interaction F(1,8.1)=0.00, p=0.9836
  (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=0.8523, slope diff=+0.001651)
Paper (N=24, count): interaction t(227)=2.68, F(1)=7.12, p=0.008.
