Non convergency of sem model, how can i troubleshoot

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emmamha...@gmail.com

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Jun 14, 2018, 8:24:15 AM6/14/18
to lavaan
I have a problem, my model can't converge. See the arguments below and output given. how can trouble shoot this?

# SEM 
> model.sem <- '
+ ###Measuremement models
+ 
+ Immediate_causes =~ morb + month_bf + num_semfood
+ Underlying_causes =~ bmi + birth_weight + bord
+ Basic_causes =~ HH_members + w_index +m_educa
+ 
+ ### Regression
+ 
+ HAZ ~ Immediate_causes + Underlying_causes + Basic_causes
+ 
+ 
+ ###Residual correlation
+ 
+ '
> fitsem <- sem(model.sem, data=data4R)
Warning messages:
1: In lav_data_full(data = data, group = group, cluster = cluster,  :
  lavaan WARNING: some observed variances are (at least) a factor 1000 times larger than others; use varTable(fit) to investigate
2: In lav_model_vcov(lavmodel = lavmodel, lavsamplestats = lavsamplestats,  :
  lavaan WARNING: could not compute standard errors!
  lavaan NOTE: this may be a symptom that the model is not identified.

3: In lav_object_post_check(object) :
  lavaan WARNING: some estimated lv variances are negative
> summary (fitsem)
lavaan (0.6-1) converged normally after 874 iterations

                                                  Used       Total
  Number of observations                          1540        3047

  Estimator                                         ML
  Model Fit Test Statistic                     655.916
  Degrees of freedom                                30
  P-value (Chi-square)                           0.000

Parameter Estimates:

  Information                                 Expected
  Information saturated (h1) model          Structured
  Standard Errors                             Standard

Latent Variables:
                       Estimate    Std.Err  z-value  P(>|z|)
  Immediate_causes =~                                       
    morb                    1.000                           
    month_bf               21.565       NA                  
    num_semfood             2.906       NA                  
  Underlying_causes =~                                      
    bmi                     1.000                           
    birth_weight          265.130       NA                  
    bord                    2.112       NA                  
  Basic_causes =~                                           
    HH_members              1.000                           
    w_index                -4.917       NA                  
    m_educa               162.557       NA                  

Regressions:
                   Estimate    Std.Err  z-value  P(>|z|)
  HAZ ~                                                 
    Immediate_cass   -134.195       NA                  
    Underlying_css     16.096       NA                  
    Basic_causes      -99.388       NA                  

Covariances:
                       Estimate    Std.Err  z-value  P(>|z|)
  Immediate_causes ~~                                       
    Underlying_css         -0.004       NA                  
    Basic_causes           -0.000       NA                  
  Underlying_causes ~~                                      
    Basic_causes           -0.001       NA                  

Variances:
                   Estimate    Std.Err  z-value  P(>|z|)
   .morb                2.533       NA                  
   .month_bf            7.182       NA                  
   .num_semfood         2.422       NA                  
   .bmi                10.660       NA                  
   .birth_weight   448275.026       NA                  
   .bord                2.036       NA                  
   .HH_members          4.444       NA                  
   .w_index             2.011       NA                  
   .m_educa            11.692       NA                  
   .HAZ             20577.163       NA                  
    Immediate_cass      0.071       NA                  
    Underlying_css      0.400       NA                  
    Basic_causes       -0.000       NA                  


Yves Rosseel

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Jun 14, 2018, 8:39:12 AM6/14/18
to lav...@googlegroups.com
On 06/14/2018 02:24 PM, emmamha...@gmail.com wrote:
> I have a problem, my model can't converge. See the arguments below and
> output given. how can trouble shoot this?

Rescale your variables. Note the warning message:

"some observed variances are (at least) a factor 1000 times larger than
others"

Rescale simply by dividing by a constant (say, 100), so that all
variables more or less have the same scale. And run again.

As an alternative, if you install the development version (0.6-2), you
can try out the (new) option optim.parscale = "stand", which may (or
not) fix this. Let me know.

Yves.
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