==============================================================================
PHASED days x tDCS LME -- mergeA2 (Box-B2 vs Box-A2)
==============================================================================
model per phase: success ~ dayp*tDCS + (1|subject)  [dayp = day - phaseStart]

phase     N  A2slope B2slope  day p     tDCS(lvl) p  interaction p  slopeDiff [95% CI]
--------------------------------------------------------------------------------------------
0-5      8   10.54   15.16  1.5e-10   0.693        0.014         +4.62 [+1.00, +8.24]
6-10     7    3.17    4.83  0.035     0.127        0.390         +1.66 [-2.22, +5.53]
6-13     7    2.92    4.47  0.00032   0.125        0.118         +1.55 [-0.41, +3.52]

Note: the interaction p (and CI) use fitlme observation-level DF and are
ANTICONSERVATIVE at these small subject counts (see tdcs_power_sim). 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
    381.01    392.23    -184.5           369.01  

Fixed effects coefficients (95% CIs):
    Name                   Estimate    SE        tStat      DF    pValue    
    {'(Intercept)'}          10.06      4.465      2.253    44      0.029296
    {'dayp'       }         10.543       1.27     8.3016    44    1.4943e-10
    {'tDCS'       }        -2.5119     6.3144    -0.3978    44        0.6927
    {'dayp:tDCS'  }         4.6214      1.796     2.5731    44      0.013526


    Lower      Upper 
      1.061    19.058
     7.9834    13.102
    -15.238    10.214
     1.0018    8.2411

Random effects covariance parameters (95% CIs):
Group: subject (8 Levels)
    Name1                  Name2                  Type           Estimate
    {'(Intercept)'}        {'(Intercept)'}        {'std'}        4.5394  


    Lower     Upper 
    1.7406    11.838

Group: Error
    Name               Estimate    Lower     Upper 
    {'Res Std'}        10.625      8.5345    13.229


==============================================================================
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
    265.24    274.57    -126.62          253.24  

Fixed effects coefficients (95% CIs):
    Name                   Estimate    SE        tStat      DF    pValue    
    {'(Intercept)'}        75.867      4.9313     15.385    31    4.6291e-16
    {'dayp'       }        3.1667      1.4366     2.2043    31      0.035054
    {'tDCS'       }        10.233      6.5234     1.5687    31       0.12687
    {'dayp:tDCS'  }        1.6583      1.9004    0.87262    31       0.38958


    Lower      Upper 
     65.809    85.924
    0.23676    6.0966
    -3.0713    23.538
    -2.2176    5.5342

Random effects covariance parameters (95% CIs):
Group: subject (7 Levels)
    Name1                  Name2                  Type           Estimate
    {'(Intercept)'}        {'(Intercept)'}        {'std'}        5.9837  


    Lower     Upper
    2.9396    12.18

Group: Error
    Name               Estimate    Lower     Upper 
    {'Res Std'}        7.8684      6.0554    10.224


==============================================================================
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
    367.22    378.69    -177.61          355.22  

Fixed effects coefficients (95% CIs):
    Name                   Estimate    SE         tStat     DF    pValue    
    {'(Intercept)'}          76.4       4.9765    15.352    46    1.0096e-19
    {'dayp'       }        2.9189      0.74973    3.8932    46    0.00031772
    {'tDCS'       }        10.289       6.5773    1.5643    46       0.12459
    {'dayp:tDCS'  }         1.554      0.97562    1.5928    46       0.11805


    Lower       Upper 
      66.382    86.417
      1.4097     4.428
     -2.9502    23.528
    -0.40985    3.5178

Random effects covariance parameters (95% CIs):
Group: subject (7 Levels)
    Name1                  Name2                  Type           Estimate
    {'(Intercept)'}        {'(Intercept)'}        {'std'}        7.1357  


    Lower     Upper 
    3.9247    12.974

Group: Error
    Name               Estimate    Lower     Upper 
    {'Res Std'}        7.3202      5.9279    9.0395