model = 
<strong>Generalized linear mixed-effects model fit by PL</strong>

<strong>Model information:</strong>
    Number of observations              30
    Fixed effects coefficients           6
    Random effects coefficients          0
    Covariance parameters                1
    Distribution                    Normal
    Link                            Identity
    FitMethod                       MPL   

<strong>Formula:</strong>
    awakening_ratio ~ 1 + genotype*state

<strong>Model fit statistics:</strong>
    AIC       BIC      LogLikelihood    Deviance
    29.622    39.43    -7.811           15.622  
<strong>Fixed effects coefficients (95% CIs):</strong>
    Name                                        Estimate       SE         tStat         DF    pValue        Lower       Upper  
    {'(Intercept)'                     }          -0.014502    0.12816      -0.11315    24       0.91085    -0.27902    0.25001
    {'genotype_WT'                     }        -0.00065426    0.20264    -0.0032286    24       0.99745    -0.41889    0.41758
    {'state_IS awakening'              }               -1.8    0.18125       -9.9308    24    5.6281e-10      -2.174    -1.4259
    {'state_NREM awakening'            }            -2.7337    0.18125       -15.082    24    9.6347e-14     -3.1078    -2.3596
    {'genotype_WT:state_IS awakening'  }            0.40585    0.28658        1.4162    24       0.16957    -0.18563    0.99732
    {'genotype_WT:state_NREM awakening'}            0.13679    0.28658        0.4773    24       0.63746    -0.45469    0.72826
<strong>Random effects covariance parameters:</strong>
Group: Error
    Name                        Estimate
    {'sqrt(Dispersion)'}        0.31393