model = 
<strong>Linear mixed-effects model fit by ML</strong>

<strong>Model information:</strong>
    Number of observations            1275
    Fixed effects coefficients           5
    Random effects coefficients          0
    Covariance parameters                1

<strong>Formula:</strong>
    response ~ 1 + State

<strong>Model fit statistics:</strong>
    AIC       BIC       LogLikelihood    Deviance
    9598.4    9629.3    -4793.2          9586.4  
<strong>Fixed effects coefficients (95% CIs):</strong>
    Name                            Estimate    SE         tStat      DF      pValue         Lower      Upper  
    {'(Intercept)'         }         16.711     0.62857     26.587    1270    3.5067e-124     15.478     17.945
    {'State_whisking'      }        -3.8612     0.73888    -5.2257    1270     2.0264e-07    -5.3108    -2.4116
    {'State_is:awakening'  }         3.2048      1.0771     2.9755    1270      0.0029801     1.0918     5.3179
    {'State_nrem:awakening'}         3.8353      1.4911     2.5722    1270       0.010219    0.91007     6.7605
    {'State_rem:awakening' }         8.4915      1.2786     6.6411    1270     4.6031e-11     5.9831         11
<strong>Random effects covariance parameters (95% CIs):</strong>
Group: Error
    Name               Estimate    Lower     Upper 
    {'Res Std'}        10.386      9.9903    10.797