==============================================================================
PHASED days x tDCS LME -- mergeB2 (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     8  9.86 14.65  2.9e-08  0.399    0.013     0.013      0.088     +4.79 [+1.06,+8.53]
6-10    7  2.40  4.80  0.18     0.142    0.253     0.254      0.328     +2.40 [-1.80,+6.60]
6-13    7  1.71  4.42  0.083    0.127    0.018     0.018      0.024     +2.71 [+0.50,+4.93]

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              48
    Fixed effects coefficients           4
    Random effects coefficients          8
    Covariance parameters                2

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

Model fit statistics:
    AIC       BIC       LogLikelihood    Deviance
    383.06    394.29    -185.53          371.06  

Fixed effects coefficients (95% CIs):
    Name                   Estimate    SE        tStat       DF    pValue    
    {'(Intercept)'}         12.524     5.5254      2.2666    44      0.028385
    {'dayp'       }         9.8571     1.4654      6.7268    44    2.8783e-08
    {'tDCS'       }        -5.9524     6.9892    -0.85166    44       0.39902
    {'dayp:tDCS'  }         4.7943     1.8536      2.5865    44      0.013079


    Lower      Upper 
     1.3881     23.66
     6.9039     12.81
    -20.038    8.1334
     1.0587    8.5299

Random effects covariance parameters (95% CIs):
Group: subject (8 Levels)
    Name1                  Name2                  Type           Estimate
    {'(Intercept)'}        {'(Intercept)'}        {'std'}        5.7044  


    Lower     Upper 
    2.6066    12.484

Group: Error
    Name               Estimate    Lower     Upper 
    {'Res Std'}        10.618      8.5282    13.219


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

Linear mixed-effects model fit by ML

Model information:
    Number of observations              35
    Fixed effects coefficients           4
    Random effects coefficients          7
    Covariance parameters                2

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

Model fit statistics:
    AIC       BIC       LogLikelihood    Deviance
    264.22    273.56    -126.11          252.22  

Fixed effects coefficients (95% CIs):
    Name                   Estimate    SE        tStat     DF    pValue    
    {'(Intercept)'}         74.2       5.8956    12.586    31    1.0133e-13
    {'dayp'       }          2.4       1.7415    1.3781    31       0.17803
    {'tDCS'       }        10.52       6.9757    1.5081    31       0.14166
    {'dayp:tDCS'  }          2.4       2.0606    1.1647    31       0.25302


    Lower      Upper 
     62.176    86.224
    -1.1518    5.9518
    -3.7071    24.747
    -1.8026    6.6026

Random effects covariance parameters (95% CIs):
Group: subject (7 Levels)
    Name1                  Name2                  Type           Estimate
    {'(Intercept)'}        {'(Intercept)'}        {'std'}        5.7551  


    Lower     Upper 
    2.7955    11.848

Group: Error
    Name               Estimate    Lower     Upper
    {'Res Std'}        7.7883      5.9937    10.12


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

Linear mixed-effects model fit by ML

Model information:
    Number of observations              50
    Fixed effects coefficients           4
    Random effects coefficients          7
    Covariance parameters                2

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

Model fit statistics:
    AIC       BIC       LogLikelihood    Deviance
    362.57    374.04    -175.28          350.57  

Fixed effects coefficients (95% CIs):
    Name                   Estimate    SE         tStat     DF    pValue    
    {'(Intercept)'}        75.168       5.6188    13.378    46    1.8212e-17
    {'dayp'       }         1.712      0.96716    1.7701    46      0.083338
    {'tDCS'       }        10.291       6.6299    1.5522    46       0.12747
    {'dayp:tDCS'  }        2.7116       1.1009    2.4631    46      0.017575


    Lower       Upper 
      63.858    86.478
    -0.23482    3.6588
     -3.0544    23.636
     0.49565    4.9275

Random effects covariance parameters (95% CIs):
Group: subject (7 Levels)
    Name1                  Name2                  Type           Estimate
    {'(Intercept)'}        {'(Intercept)'}        {'std'}        6.379   


    Lower     Upper 
    3.4793    11.695

Group: Error
    Name               Estimate    Lower     Upper 
    {'Res Std'}        7.0508      5.7111    8.7047