\begin{Schunk}
\begin{Sinput}
 Nboot <- 500
 mediat.out.2 <- sem(mediat.mod.2, data = dat,
                      std.lv = TRUE, se = "boot", bootstrap = Nboot)
 summary(mediat.out.2, standardized = TRUE, fit = TRUE)
\end{Sinput}
\begin{Soutput}
lavaan (0.5-23.1097) converged normally after  62 iterations

  Number of observations                           380

  Estimator                                         ML
  Minimum Function Test Statistic              109.152
  Degrees of freedom                                83
  P-value (Chi-square)                           0.029

Model test baseline model:

  Minimum Function Test Statistic             3749.411
  Degrees of freedom                               105
  P-value                                        0.000

User model versus baseline model:

  Comparative Fit Index (CFI)                    0.993
  Tucker-Lewis Index (TLI)                       0.991

Loglikelihood and Information Criteria:

  Loglikelihood user model (H0)              -3700.262
  Loglikelihood unrestricted model (H1)      -3645.686

  Number of free parameters                         37
  Akaike (AIC)                                7474.524
  Bayesian (BIC)                              7620.310
  Sample-size adjusted Bayesian (BIC)         7502.917

Root Mean Square Error of Approximation:

  RMSEA                                          0.029
  90 Percent Confidence Interval          0.010  0.043
  P-value RMSEA <= 0.05                          0.996

Standardized Root Mean Square Residual:

  SRMR                                           0.034

Parameter Estimates:

  Information                                 Observed
  Standard Errors                            Bootstrap
  Number of requested bootstrap draws              500
  Number of successful bootstrap draws             500

Latent Variables:
                   Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
  Agency =~                                                             
    Agency1           0.466    0.022   21.169    0.000    0.466    0.905
    Agency2           0.492    0.023   21.447    0.000    0.492    0.933
    Agency3           0.497    0.024   20.379    0.000    0.497    0.912
  Intrinsic =~                                                          
    Intrin1           0.466    0.036   12.839    0.000    0.540    0.703
    Intrin2           0.500    0.036   13.803    0.000    0.580    0.682
    Intrin3           0.531    0.032   16.582    0.000    0.616    0.800
  Extrinsic =~                                                          
    Extrin1           0.373    0.024   15.742    0.000    0.388    0.808
    Extrin2           0.440    0.029   15.089    0.000    0.457    0.793
    Extrin3           0.454    0.030   14.985    0.000    0.471    0.827
  Positive =~                                                           
    PosAFF1           0.514    0.026   19.572    0.000    0.569    0.854
    PosAFF2           0.545    0.031   17.524    0.000    0.604    0.882
    PosAFF3           0.570    0.028   20.166    0.000    0.632    0.895
  Negative =~                                                           
    NegAFF1           0.620    0.040   15.578    0.000    0.633    0.889
    NegAFF2           0.573    0.040   14.290    0.000    0.585    0.883
    NegAFF3           0.586    0.033   17.494    0.000    0.598    0.918

Regressions:
                   Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
  Positive ~                                                            
    Intrinsic (b1)    0.343    0.076    4.515    0.000    0.359    0.359
    Agency            0.129    0.076    1.692    0.091    0.116    0.116
  Negative ~                                                            
    Extrinsic (b2)    0.199    0.070    2.860    0.004    0.202    0.202
  Intrinsic ~                                                           
    Agency    (a1)    0.588    0.086    6.862    0.000    0.507    0.507
  Extrinsic ~                                                           
    Agency    (a2)    0.278    0.065    4.256    0.000    0.268    0.268

Covariances:
                   Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
 .Intrinsic ~~                                                          
   .Extrinsic        -0.202    0.062   -3.273    0.001   -0.202   -0.202
 .Positive ~~                                                           
   .Negative         -0.076    0.071   -1.080    0.280   -0.076   -0.076

Variances:
                   Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
   .Agency1           0.048    0.005    8.888    0.000    0.048    0.181
   .Agency2           0.036    0.005    7.911    0.000    0.036    0.129
   .Agency3           0.050    0.006    8.711    0.000    0.050    0.169
   .Intrin1           0.299    0.031    9.583    0.000    0.299    0.506
   .Intrin2           0.387    0.038   10.179    0.000    0.387    0.535
   .Intrin3           0.213    0.035    6.060    0.000    0.213    0.359
   .Extrin1           0.080    0.011    7.223    0.000    0.080    0.348
   .Extrin2           0.123    0.015    8.003    0.000    0.123    0.372
   .Extrin3           0.103    0.017    5.936    0.000    0.103    0.317
   .PosAFF1           0.121    0.015    8.063    0.000    0.121    0.271
   .PosAFF2           0.104    0.016    6.528    0.000    0.104    0.222
   .PosAFF3           0.099    0.015    6.734    0.000    0.099    0.199
   .NegAFF1           0.107    0.016    6.838    0.000    0.107    0.210
   .NegAFF2           0.096    0.013    7.592    0.000    0.096    0.219
   .NegAFF3           0.067    0.011    6.015    0.000    0.067    0.158
    Agency            1.000                               1.000    1.000
   .Intrinsic         1.000                               0.743    0.743
   .Extrinsic         1.000                               0.928    0.928
   .Positive          1.000                               0.815    0.815
   .Negative          1.000                               0.959    0.959

Defined Parameters:
                   Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
    ind1              0.202    0.047    4.331    0.000    0.182    0.182
    ind2              0.055    0.023    2.447    0.014    0.054    0.054
\end{Soutput}
\end{Schunk}
