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

<strong>Model information:</strong>
    Number of observations            1062
    Fixed effects coefficients           5
    Random effects coefficients          0
    Covariance parameters                1

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

<strong>Model fit statistics:</strong>
    AIC       BIC       LogLikelihood    Deviance
    5850.9    5880.7    -2919.4          5838.9  
<strong>Fixed effects coefficients (95% CIs):</strong>
    Name                            Estimate    SE         tStat      DF      pValue        Lower      Upper  
    {'(Intercept)'         }          2.0307    0.25097     8.0913    1057    1.6104e-15     1.5382     2.5232
    {'State_whisking'      }        -0.43081    0.29846    -1.4435    1057       0.14919    -1.0165    0.15483
    {'State_is:awakening'  }         -3.4546    0.40545    -8.5203    1057    5.4191e-17    -4.2501     -2.659
    {'State_nrem:awakening'}         -2.9629    0.55256    -5.3621    1057    1.0101e-07    -4.0471    -1.8786
    {'State_rem:awakening' }        -0.80579    0.47679      -1.69    1057      0.091321    -1.7414    0.12978
<strong>Random effects covariance parameters (95% CIs):</strong>
Group: Error
    Name               Estimate    Lower     Upper 
    {'Res Std'}        3.7813      3.6238    3.9456