\begin{Schunk}
\begin{Sinput}
 ## Specifying the model structure
 sem.gotBully <- '
  gotBully =~ NA*gotBu1_i + gotBu2_i + gotBu3_i + gotBu4_i + gotBu5_i + gotBu6_i + gotBu7_i + gotBu8_i + gotBu9_i
                  
  gotBully ~~ 1*gotBully
  gotBully ~ Age '
 ## Fitting the model
 ## Listwise deletion is used to compare the results with MLM
 sem.gotBully.fit <- sem(model = sem.gotBully, data = hbsc.2, mimic = "Mplus", missing = "listwise")
 ## Requesting an estimation summary
 summary(sem.gotBully.fit, fit.measures = TRUE, standardized = TRUE) 
\end{Sinput}
\begin{Soutput}
lavaan 0.6-3 ended normally after 18 iterations

  Optimization method                           NLMINB
  Number of free parameters                         19

                                                  Used       Total
  Number of observations                           238         333

  Estimator                                         ML
  Model Fit Test Statistic                     257.449
  Degrees of freedom                                35
  P-value (Chi-square)                           0.000

Model test baseline model:

  Minimum Function Test Statistic             1269.025
  Degrees of freedom                                45
  P-value                                        0.000

User model versus baseline model:

  Comparative Fit Index (CFI)                    0.818
  Tucker-Lewis Index (TLI)                       0.766

Loglikelihood and Information Criteria:

  Loglikelihood user model (H0)              -2878.099
  Loglikelihood unrestricted model (H1)      -2749.375

  Number of free parameters                         19
  Akaike (AIC)                                5794.199
  Bayesian (BIC)                              5860.172
  Sample-size adjusted Bayesian (BIC)         5799.948

Root Mean Square Error of Approximation:

  RMSEA                                          0.163
  90 Percent Confidence Interval          0.145  0.182
  P-value RMSEA <= 0.05                          0.000

Standardized Root Mean Square Residual:

  SRMR                                           0.076

Parameter Estimates:

  Information                                 Expected
  Information saturated (h1) model          Structured
  Standard Errors                             Standard

Latent Variables:
                   Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
  gotBully =~                                                           
    gotBu1_i          0.782    0.086    9.071    0.000    0.798    0.562
    gotBu2_i          0.818    0.079   10.363    0.000    0.835    0.627
    gotBu3_i          0.811    0.062   13.159    0.000    0.828    0.750
    gotBu4_i          0.928    0.080   11.562    0.000    0.948    0.682
    gotBu5_i          0.931    0.063   14.677    0.000    0.951    0.809
    gotBu6_i          0.810    0.055   14.749    0.000    0.827    0.811
    gotBu7_i          0.902    0.077   11.730    0.000    0.921    0.690
    gotBu8_i          0.684    0.054   12.668    0.000    0.698    0.730
    gotBu9_i          0.684    0.054   12.648    0.000    0.699    0.729

Regressions:
                   Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
  gotBully ~                                                            
    Age              -0.142    0.048   -2.988    0.003   -0.139   -0.201

Variances:
                   Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
   .gotBully          1.000                               0.959    0.959
   .gotBu1_i          1.378    0.132   10.418    0.000    1.378    0.684
   .gotBu2_i          1.078    0.106   10.221    0.000    1.078    0.607
   .gotBu3_i          0.533    0.056    9.533    0.000    0.533    0.437
   .gotBu4_i          1.030    0.103    9.981    0.000    1.030    0.534
   .gotBu5_i          0.478    0.054    8.883    0.000    0.478    0.346
   .gotBu6_i          0.355    0.040    8.844    0.000    0.355    0.342
   .gotBu7_i          0.934    0.094    9.941    0.000    0.934    0.524
   .gotBu8_i          0.427    0.044    9.690    0.000    0.427    0.467
   .gotBu9_i          0.430    0.044    9.696    0.000    0.430    0.468
\end{Soutput}
\end{Schunk}
