\begin{Schunk}
\begin{Sinput}
 mediat.out.3 <- sem(mediat.mod.3, data = dat,
                      std.lv = TRUE, se = "boot", bootstrap = Nboot)
 summary(mediat.out.3, standardized = TRUE, fit = TRUE)
\end{Sinput}
\begin{Soutput}
lavaan (0.5-23.1097) converged normally after 480 iterations

  Number of observations                           380

  Estimator                                         ML
  Minimum Function Test Statistic              118.955
  Degrees of freedom                                84
  P-value (Chi-square)                           0.007

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)                    0.990
  Tucker-Lewis Index (TLI)                       0.988

Loglikelihood and Information Criteria:

  Loglikelihood user model (H0)              -3705.163
  Loglikelihood unrestricted model (H1)      -3645.686

  Number of free parameters                         36
  Akaike (AIC)                                7482.326
  Bayesian (BIC)                              7624.172
  Sample-size adjusted Bayesian (BIC)         7509.951

Root Mean Square Error of Approximation:

  RMSEA                                          0.033
  90 Percent Confidence Interval          0.018  0.046
  P-value RMSEA <= 0.05                          0.986

Standardized Root Mean Square Residual:

  SRMR                                           0.051

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           0.467    0.021   22.738    0.000    0.467    0.905
    Agency2           0.491    0.020   24.518    0.000    0.491    0.933
    Agency3           0.497    0.022   22.271    0.000    0.497    0.911
  Intrinsic =~                                                          
    Intrin1           0.468    0.041   11.435    0.000    0.528    0.693
    Intrin2           0.508    0.036   14.071    0.000    0.573    0.679
    Intrin3           0.540    0.032   16.825    0.000    0.609    0.801
  Extrinsic =~                                                          
    Extrin1           0.373    0.023   15.931    0.000    0.395    0.813
    Extrin2           0.439    0.029   15.095    0.000    0.465    0.798
    Extrin3           0.452    0.029   15.606    0.000    0.478    0.829
  Positive =~                                                           
    PosAFF1           0.530    0.024   21.669    0.000    0.564    0.853
    PosAFF2           0.562    0.028   19.847    0.000    0.598    0.881
    PosAFF3           0.587    0.028   21.244    0.000    0.624    0.892
  Negative =~                                                           
    NegAFF1           0.614    0.038   15.994    0.000    0.639    0.890
    NegAFF2           0.567    0.039   14.484    0.000    0.590    0.885
    NegAFF3           0.579    0.037   15.774    0.000    0.603    0.919

Regressions:
                   Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
  Positive ~                                                            
    Intrinsic (b1)    0.183    0.078    2.347    0.019    0.194    0.194
    Agency            0.218    0.077    2.831    0.005    0.205    0.205
  Negative ~                                                            
    Extrinsic (b2)    0.275    0.056    4.961    0.000    0.280    0.280
  Intrinsic ~                                                           
    Agency    (a1)    0.523    0.104    5.041    0.000    0.463    0.463
  Extrinsic ~                                                           
    Agency    (a2)    0.348    0.064    5.462    0.000    0.328    0.328

Covariances:
                   Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
 .Intrinsic ~~                                                          
   .Extrinsic        -0.202    0.064   -3.163    0.002   -0.202   -0.202
 .Positive ~~                                                           
   .Negative         -0.063    0.070   -0.909    0.363   -0.063   -0.063

Variances:
                   Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
   .Agency1           0.048    0.006    8.495    0.000    0.048    0.181
   .Agency2           0.036    0.005    7.550    0.000    0.036    0.129
   .Agency3           0.050    0.006    8.839    0.000    0.050    0.170
   .Intrin1           0.301    0.033    9.066    0.000    0.301    0.519
   .Intrin2           0.383    0.039    9.800    0.000    0.383    0.539
   .Intrin3           0.208    0.039    5.373    0.000    0.208    0.359
   .Extrin1           0.080    0.010    7.633    0.000    0.080    0.339
   .Extrin2           0.123    0.016    7.500    0.000    0.123    0.363
   .Extrin3           0.104    0.017    6.180    0.000    0.104    0.312
   .PosAFF1           0.120    0.016    7.510    0.000    0.120    0.273
   .PosAFF2           0.103    0.016    6.352    0.000    0.103    0.224
   .PosAFF3           0.100    0.014    7.035    0.000    0.100    0.205
   .NegAFF1           0.107    0.016    6.657    0.000    0.107    0.207
   .NegAFF2           0.096    0.013    7.209    0.000    0.096    0.216
   .NegAFF3           0.067    0.011    6.245    0.000    0.067    0.156
    Agency            1.000                               1.000    1.000
   .Intrinsic         1.000                               0.785    0.785
   .Extrinsic         1.000                               0.892    0.892
   .Positive          1.000                               0.883    0.883
   .Negative          1.000                               0.922    0.922

Defined Parameters:
                   Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
    ind1              0.096    0.026    3.708    0.000    0.090    0.090
    ind2              0.096    0.026    3.708    0.000    0.092    0.092

Constraints:
                                               |Slack|
    ind1 - (ind2)                                0.000
\end{Soutput}
\end{Schunk}
