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I'm running SEM in lavaan, but my model seems not fitting correctly based on the chi-square value and it's p-val = 0.000.

When i look at other fit measurements, the model is close to fit well. Below is my model, can someone help me out to interoperate my results? Based on this information i have information to say that the model is ok, but also.... not based on the chi-square.

any help would be much appreciated!

lavaan 0.6-12 ended normally after 127 iterations

  Estimator                                         ML
  Optimization method                           NLMINB
  Number of model parameters                        72

  Number of observations                           275

Model Test User Model:
                                              Standard      Robust
  Test Statistic                               409.000     370.066
  Degrees of freedom                               218         218
  P-value (Chi-square)                           0.000       0.000
  Scaling correction factor                                  1.105
    Satorra-Bentler correction                                    

Model Test Baseline Model:

  Test statistic                              1962.734    1643.739
  Degrees of freedom                               250         250
  P-value                                        0.000       0.000
  Scaling correction factor                                  1.194

User Model versus Baseline Model:

  Comparative Fit Index (CFI)                    0.888       0.891
  Tucker-Lewis Index (TLI)                       0.872       0.875
                                                                  
  Robust Comparative Fit Index (CFI)                         0.899
  Robust Tucker-Lewis Index (TLI)                            0.884

Loglikelihood and Information Criteria:

  Loglikelihood user model (H0)             -23956.022  -23956.022
  Loglikelihood unrestricted model (H1)     -23751.523  -23751.523
                                                                  
  Akaike (AIC)                               48056.045   48056.045
  Bayesian (BIC)                             48316.452   48316.452
  Sample-size adjusted Bayesian (BIC)        48088.154   48088.154

Root Mean Square Error of Approximation:

  RMSEA                                          0.056       0.050
  90 Percent confidence interval - lower         0.048       0.042
  90 Percent confidence interval - upper         0.065       0.059
  P-value RMSEA <= 0.05                          0.103       0.461
                                                                  
  Robust RMSEA                                               0.053
  90 Percent confidence interval - lower                     0.044
  90 Percent confidence interval - upper                     0.062

Standardized Root Mean Square Residual:

  SRMR                                           0.070       0.070

Parameter Estimates:

  Standard errors                           Robust.sem
  Information                                 Expected
  Information saturated (h1) model          Structured

Latent Variables:
                   Estimate   Std.Err  z-value  P(>|z|)   Std.lv   Std.all
  Att_x =~                                                                
    ATT_good_100      12.691    1.715    7.402    0.000    12.691    0.827
    ATT_mprtnt_100    14.437    2.035    7.094    0.000    14.437    0.866
    self_1_100         8.571    1.944    4.410    0.000     8.571    0.464
    self_2_100         7.845    1.505    5.213    0.000     7.845    0.389
    ATT_useful_100    13.505    1.613    8.375    0.000    13.505    0.678
    self_4_100        10.289    2.030    5.068    0.000    10.289    0.451
  PBC_x =~                                                                
    PBC_time_100      15.549    1.298   11.975    0.000    15.549    0.768
    PBC_space_100     20.148    1.692   11.908    0.000    20.148    0.672
    ATT_plesnt_100     8.259    1.905    4.335    0.000     8.259    0.338
    ATT_hygenc_100    -9.277    1.748   -5.307    0.000    -9.277   -0.348
  Soc_x =~                                                                
    MN_friend_100     26.891    1.156   23.261    0.000    26.891    0.923
    MN_colleg_100     22.978    1.424   16.137    0.000    22.978    0.801
    MN_family_100     19.583    1.678   11.669    0.000    19.583    0.630
    MN_media_100      17.132    1.654   10.355    0.000    17.132    0.613
  Know_x =~                                                               
    PBC_easy_100      15.685    1.405   11.163    0.000    15.685    0.766
    PBC_knw_wh_100    10.038    1.019    9.848    0.000    10.038    0.626
    PBC_knw_hw_100    13.559    1.210   11.203    0.000    13.559    0.744
    satis_3_100       14.222    1.771    8.030    0.000    14.222    0.558

Regressions:
                   Estimate   Std.Err  z-value  P(>|z|)   Std.lv   Std.all
  Intention_100 ~                                                         
    Att_x              1.829    1.158    1.579    0.114     1.829    0.106
    PBC_x              6.713    1.094    6.137    0.000     6.713    0.389
    Soc_x              2.693    1.171    2.300    0.021     2.693    0.156
    dist_pak           0.006    0.003    2.398    0.016     0.006    0.094
  Beh_avg ~                                                               
    Intention_100      0.200    0.078    2.577    0.010     0.200    0.211
    PBC_x              5.199    1.272    4.089    0.000     5.199    0.317
    PANT               8.536    3.000    2.845    0.004     8.536    0.165
    dist_org          -0.026    0.007   -3.576    0.000    -0.026   -0.199

Covariances:
                   Estimate   Std.Err  z-value  P(>|z|)   Std.lv   Std.all
  Att_x ~~                                                                
    PBC_x              0.335    0.070    4.801    0.000     0.335    0.335
    Soc_x              0.089    0.070    1.256    0.209     0.089    0.089
    Know_x             0.257    0.073    3.518    0.000     0.257    0.257
  PBC_x ~~                                                                
    Soc_x             -0.016    0.075   -0.208    0.836    -0.016   -0.016
    Know_x             0.565    0.068    8.274    0.000     0.565    0.565
  Soc_x ~~                                                                
    Know_x            -0.013    0.079   -0.168    0.866    -0.013   -0.013  
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1 Answer 1

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The fit does not look too good. I would take a look at the standardized residuals and/or modification indices to examine the sources of misfit. Some of your factor indicators have rather small standardized loadings (especially the ones that are supposed to measure the factors Att_x and PBC_x). There may be some inhomogeneities in your measures.

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