\begin{Schunk}
\begin{Sinput}
 ## Estimating cfa.01.v.02
 ## With pairwise deletion
 cfa.01.v.02.fit.pairwise <- 
  cfa(model = cfa.01.v.02, data = depre_i_miss,
      mimic = "Mplus", estimator = "WLSMV",
      missing = "pairwise", meanstructure = TRUE,
      ordered = c("depre1_i", "depre2_i",
                  "depre3_i", "depre4_i",                 
                  "depre5_i", "depre6_i"))
 summary(cfa.01.v.02.fit.pairwise, fit.measures = TRUE,
          standardized = TRUE)
\end{Sinput}
\begin{Soutput}
lavaan 0.6-3 ended normally after 11 iterations

  Optimization method                           NLMINB
  Number of free parameters                         30

                                                  Used       Total
  Number of observations                          4220        4284
  Number of missing patterns                        57

  Estimator                                       DWLS      Robust
  Model Fit Test Statistic                     162.985     261.530
  Degrees of freedom                                 9           9
  P-value (Chi-square)                           0.000       0.000
  Scaling correction factor                                  0.624
  Shift parameter                                            0.207
    for simple second-order correction (WLSMV)

Model test baseline model:

  Minimum Function Test Statistic            14275.959   11499.317
  Degrees of freedom                                15          15
  P-value                                        0.000       0.000

User model versus baseline model:

  Comparative Fit Index (CFI)                    0.989       0.978
  Tucker-Lewis Index (TLI)                       0.982       0.963

  Robust Comparative Fit Index (CFI)                            NA
  Robust Tucker-Lewis Index (TLI)                               NA

Root Mean Square Error of Approximation:

  RMSEA                                          0.064       0.082
  90 Percent Confidence Interval          0.055  0.072       0.073  0.090
  P-value RMSEA <= 0.05                          0.004       0.000

  Robust RMSEA                                                  NA
  90 Percent Confidence Interval                                NA     NA

Standardized Root Mean Square Residual:

  SRMR                                           0.035       0.035

Weighted Root Mean Square Residual:

  WRMR                                           2.044       2.044

Parameter Estimates:

  Information                                 Expected
  Information saturated (h1) model        Unstructured
  Standard Errors                           Robust.sem

Latent Variables:
                   Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
  depress =~                                                            
    depre1_i          0.710    0.011   63.181    0.000    0.710    0.710
    depre2_i          0.660    0.011   58.102    0.000    0.660    0.660
    depre3_i          0.736    0.013   56.793    0.000    0.736    0.736
    depre4_i          0.723    0.011   65.066    0.000    0.723    0.723
    depre5_i          0.599    0.013   44.771    0.000    0.599    0.599
    depre6_i          0.584    0.013   43.556    0.000    0.584    0.584

Intercepts:
                   Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
   .depre1_i          0.000                               0.000    0.000
   .depre2_i          0.000                               0.000    0.000
   .depre3_i          0.000                               0.000    0.000
   .depre4_i          0.000                               0.000    0.000
   .depre5_i          0.000                               0.000    0.000
   .depre6_i          0.000                               0.000    0.000
    depress           0.000                               0.000    0.000

Thresholds:
                   Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
    depre1_i|t1      -0.558    0.022  -25.930    0.000   -0.558   -0.558
    depre1_i|t2       0.136    0.020    6.663    0.000    0.136    0.136
    depre1_i|t3       1.095    0.025   43.024    0.000    1.095    1.095
    depre1_i|t4       1.792    0.038   47.133    0.000    1.792    1.792
    depre2_i|t1      -0.869    0.023  -37.153    0.000   -0.869   -0.869
    depre2_i|t2      -0.185    0.020   -9.043    0.000   -0.185   -0.185
    depre2_i|t3       0.735    0.022   32.725    0.000    0.735    0.735
    depre2_i|t4       1.508    0.031   47.990    0.000    1.508    1.508
    depre3_i|t1       0.273    0.021   13.202    0.000    0.273    0.273
    depre3_i|t2       0.649    0.022   29.423    0.000    0.649    0.649
    depre3_i|t3       1.164    0.026   44.216    0.000    1.164    1.164
    depre3_i|t4       1.614    0.034   47.863    0.000    1.614    1.614
    depre4_i|t1      -0.106    0.020   -5.184    0.000   -0.106   -0.106
    depre4_i|t2       0.262    0.021   12.638    0.000    0.262    0.262
    depre4_i|t3       0.888    0.024   37.534    0.000    0.888    0.888
    depre4_i|t4       1.421    0.030   47.313    0.000    1.421    1.421
    depre5_i|t1      -0.378    0.021  -18.025    0.000   -0.378   -0.378
    depre5_i|t2       0.066    0.020    3.210    0.001    0.066    0.066
    depre5_i|t3       0.664    0.022   29.966    0.000    0.664    0.664
    depre5_i|t4       1.228    0.027   45.242    0.000    1.228    1.228
    depre6_i|t1      -0.437    0.021  -20.691    0.000   -0.437   -0.437
    depre6_i|t2       0.075    0.020    3.690    0.000    0.075    0.075
    depre6_i|t3       0.739    0.023   32.792    0.000    0.739    0.739
    depre6_i|t4       1.248    0.027   45.629    0.000    1.248    1.248

Variances:
                   Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
    depress           1.000                               1.000    1.000
   .depre1_i          0.495                               0.495    0.495
   .depre2_i          0.564                               0.564    0.564
   .depre3_i          0.458                               0.458    0.458
   .depre4_i          0.478                               0.478    0.478
   .depre5_i          0.642                               0.642    0.642
   .depre6_i          0.659                               0.659    0.659

Scales y*:
                   Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
    depre1_i          1.000                               1.000    1.000
    depre2_i          1.000                               1.000    1.000
    depre3_i          1.000                               1.000    1.000
    depre4_i          1.000                               1.000    1.000
    depre5_i          1.000                               1.000    1.000
    depre6_i          1.000                               1.000    1.000
\end{Soutput}
\end{Schunk}
