lavaan 0.6.17 ended normally after 79 iterations

  Estimator                                         ML
  Optimization method                           NLMINB
  Number of model parameters                        37

  Number of observations                           449
  Number of missing patterns                         8

Model Test User Model:
                                                      
  Test statistic                               491.904
  Degrees of freedom                                75
  P-value (Chi-square)                           0.000

Model Test Baseline Model:

  Test statistic                              1836.174
  Degrees of freedom                                98
  P-value                                        0.000

User Model versus Baseline Model:

  Comparative Fit Index (CFI)                    0.760
  Tucker-Lewis Index (TLI)                       0.687
                                                      
  Robust Comparative Fit Index (CFI)             0.763
  Robust Tucker-Lewis Index (TLI)                0.690

Loglikelihood and Information Criteria:

  Loglikelihood user model (H0)              -3271.698
  Loglikelihood unrestricted model (H1)      -3027.642
                                                      
  Akaike (AIC)                                6617.395
  Bayesian (BIC)                              6769.355
  Sample-size adjusted Bayesian (SABIC)       6651.932

Root Mean Square Error of Approximation:

  RMSEA                                          0.111
  90 Percent confidence interval - lower         0.102
  90 Percent confidence interval - upper         0.121
  P-value H_0: RMSEA <= 0.050                    0.000
  P-value H_0: RMSEA >= 0.080                    1.000
                                                      
  Robust RMSEA                                   0.118
  90 Percent confidence interval - lower         0.108
  90 Percent confidence interval - upper         0.128
  P-value H_0: Robust RMSEA <= 0.050             0.000
  P-value H_0: Robust RMSEA >= 0.080             1.000

Standardized Root Mean Square Residual:

  SRMR                                           0.116

Parameter Estimates:

  Standard errors                             Standard
  Information                                 Observed
  Observed information based on                Hessian

Latent Variables:
                   Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
  iv1 =~                                                                
    rich1             0.828    0.045   18.423    0.000    0.828    0.839
    rich2             0.985    0.043   22.854    0.000    0.985    0.993
  iv2 =~                                                                
    hap1              0.846    0.055   15.325    0.000    0.846    0.745
    hap2_recoded      1.035    0.063   16.554    0.000    1.035    0.786
  iv3 =~                                                                
    mean1             1.030    0.048   21.239    0.000    1.030    0.925
    mean2             0.926    0.061   15.144    0.000    0.926    0.699

Regressions:
                   Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
  cons ~                                                                
    iv1               0.013    0.139    0.093    0.926    0.013    0.008
    iv2               0.247    0.315    0.782    0.434    0.247    0.150
    iv3              -0.459    0.353   -1.301    0.193   -0.459   -0.279
    age              -0.055    0.028   -1.974    0.048   -0.055   -0.095
    female            0.527    0.177    2.977    0.003    0.527    0.160
    asi               0.177    0.251    0.706    0.480    0.177    0.033
    black             0.888    0.295    3.008    0.003    0.888    0.139
    his               0.414    0.209    1.981    0.048    0.414    0.094
    oth               1.012    0.552    1.832    0.067    1.012    0.086
    neoe              0.036    0.052    0.684    0.494    0.036    0.036
    neoa              0.128    0.072    1.766    0.077    0.128    0.090
    neoc             -0.112    0.075   -1.495    0.135   -0.112   -0.084
    neon              0.091    0.065    1.405    0.160    0.091    0.081
    neoo              0.183    0.083    2.215    0.027    0.183    0.126

Covariances:
                   Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
  iv1 ~~                                                                
    iv2               0.513    0.047   10.992    0.000    0.513    0.513
    iv3               0.644    0.038   17.064    0.000    0.644    0.644
  iv2 ~~                                                                
    iv3               0.879    0.032   27.285    0.000    0.879    0.879

Intercepts:
                   Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
   .rich1             5.028    0.049  102.149    0.000    5.028    5.094
   .rich2             5.011    0.049  101.558    0.000    5.011    5.050
   .hap1              5.246    0.057   92.316    0.000    5.246    4.619
   .hap2_recoded      4.612    0.065   70.510    0.000    4.612    3.504
   .mean1             5.204    0.056   93.683    0.000    5.204    4.675
   .mean2             4.601    0.066   69.746    0.000    4.601    3.471
   .cons              3.356    0.938    3.579    0.000    3.356    2.040

Variances:
                   Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
   .rich1             0.289    0.040    7.159    0.000    0.289    0.297
   .rich2             0.014    0.049    0.281    0.778    0.014    0.014
   .hap1              0.574    0.059    9.696    0.000    0.574    0.445
   .hap2_recoded      0.661    0.079    8.362    0.000    0.661    0.382
   .mean1             0.179    0.050    3.608    0.000    0.179    0.144
   .mean2             0.899    0.075   12.055    0.000    0.899    0.511
   .cons              2.312    0.170   13.575    0.000    2.312    0.854
    iv1               1.000                               1.000    1.000
    iv2               1.000                               1.000    1.000
    iv3               1.000                               1.000    1.000

