==============================================================================
PHASED days x tDCS LME -- unmerged (Box-B2 vs Box-A2)
==============================================================================
model per phase: success ~ dayp*tDCS + (1|subject)  [dayp = day - phaseStart]

phase    N A2slp B2slp  day p    tDCS p   intP(res) intP(Satt) intP(RS)  slopeDiff [95% CI]
--------------------------------------------------------------------------------------------------------
0-5     6  9.86 15.22  1.6e-07  0.689    0.015     0.015      0.133     +5.36 [+1.11,+9.62]
6-10    5  2.40  4.17  0.23     0.098    0.486     0.486      0.555     +1.77 [-3.41,+6.95]
6-13    5  1.71  3.98  0.12     0.101    0.097     0.097      0.138     +2.27 [-0.44,+4.97]

Columns: intP(res)=observation-level DF (anticonservative); intP(Satt)=Satterthwaite
DF (~= residual on this random-intercept model); intP(RS)=per-animal random-slope
(dayp|subject) model, the honest test (DF collapses toward the animal count; 'n/a' if it
did not converge). The early phase carries the Box-B2 faster-acquisition signal; late
phases converge.
==============================================================================
FULL MODEL SUMMARY -- phase 0-5: success ~ dayp*tDCS + (1|subject)
==============================================================================

Linear mixed-effects model fit by ML

Model information:
    Number of observations              36
    Fixed effects coefficients           4
    Random effects coefficients          6
    Covariance parameters                2

Formula:
    success ~ 1 + dayp*tDCS + (1 | subject)

Model fit statistics:
    AIC       BIC       LogLikelihood    Deviance
    289.66    299.16    -138.83          277.66  

Fixed effects coefficients (95% CIs):
    Name                   Estimate    SE        tStat       DF    pValue    
    {'(Intercept)'}         12.524     5.2775      2.3731    32      0.023816
    {'dayp'       }         9.8571     1.4772      6.6729    32    1.5706e-07
    {'tDCS'       }        -3.0159     7.4635    -0.40408    32       0.68884
    {'dayp:tDCS'  }         5.3619      2.089      2.5667    32      0.015149


    Lower      Upper 
     1.7739    23.274
     6.8482    12.866
    -18.219    12.187
     1.1067    9.6172

Random effects covariance parameters (95% CIs):
Group: subject (6 Levels)
    Name1                  Name2                  Type           Estimate
    {'(Intercept)'}        {'(Intercept)'}        {'std'}        4.8527  


    Lower     Upper 
    1.7069    13.796

Group: Error
    Name               Estimate    Lower     Upper 
    {'Res Std'}        10.703      8.3104    13.785


==============================================================================
FULL MODEL SUMMARY -- phase 6-10: success ~ dayp*tDCS + (1|subject)
==============================================================================

Linear mixed-effects model fit by ML

Model information:
    Number of observations              25
    Fixed effects coefficients           4
    Random effects coefficients          5
    Covariance parameters                2

Formula:
    success ~ 1 + dayp*tDCS + (1 | subject)

Model fit statistics:
    AIC       BIC       LogLikelihood    Deviance
    196.97    204.29    -92.486          184.97  

Fixed effects coefficients (95% CIs):
    Name                   Estimate    SE        tStat      DF    pValue    
    {'(Intercept)'}          74.2      6.4017     11.591    21    1.3774e-10
    {'dayp'       }           2.4      1.9295     1.2439    21       0.22726
    {'tDCS'       }        14.333      8.2646     1.7343    21      0.097522
    {'dayp:tDCS'  }        1.7667       2.491    0.70923    21       0.48598


    Lower      Upper 
     60.887    87.513
    -1.6126    6.4126
    -2.8539    31.521
    -3.4136    6.9469

Random effects covariance parameters (95% CIs):
Group: subject (5 Levels)
    Name1                  Name2                  Type           Estimate
    {'(Intercept)'}        {'(Intercept)'}        {'std'}        6.1065  


    Lower     Upper 
    2.5428    14.665

Group: Error
    Name               Estimate    Lower     Upper 
    {'Res Std'}        8.6289      6.3295    11.764


==============================================================================
FULL MODEL SUMMARY -- phase 6-13: success ~ dayp*tDCS + (1|subject)
==============================================================================

Linear mixed-effects model fit by ML

Model information:
    Number of observations              34
    Fixed effects coefficients           4
    Random effects coefficients          5
    Covariance parameters                2

Formula:
    success ~ 1 + dayp*tDCS + (1 | subject)

Model fit statistics:
    AIC       BIC      LogLikelihood    Deviance
    257.04    266.2    -122.52          245.04  

Fixed effects coefficients (95% CIs):
    Name                   Estimate    SE        tStat     DF    pValue    
    {'(Intercept)'}         75.17      6.2311    12.064    30    4.8879e-13
    {'dayp'       }        1.7101       1.061    1.6117    30       0.11749
    {'tDCS'       }        13.563      8.0252      1.69    30        0.1014
    {'dayp:tDCS'  }         2.267      1.3237    1.7126    30      0.097101


    Lower       Upper 
      62.445    87.896
    -0.45682     3.877
     -2.8271    29.952
    -0.43635    4.9703

Random effects covariance parameters (95% CIs):
Group: subject (5 Levels)
    Name1                  Name2                  Type           Estimate
    {'(Intercept)'}        {'(Intercept)'}        {'std'}        7.1166  


    Lower     Upper 
    3.4834    14.539

Group: Error
    Name               Estimate    Lower     Upper 
    {'Res Std'}        7.7328      5.9847    9.9914