# Solved – How to interpret this lavaan structural equation model

I created following structural equation model from iris data set using lavaan package in R:

How do I interpret these numbers. The output (of sem() function of lavaan package) is given below. It did not give any P values:

``lavaan (0.5-18) converged normally after  64 iterations    Number of observations                           150    Estimator                                         ML   Minimum Function Test Statistic                   NA   Degrees of freedom                                -4   Minimum Function Value               0.0000000000000  Parameter estimates:    Information                                 Expected   Standard Errors                             Standard                     Estimate  Std.err  Z-value  P(>|z|) Latent variables:   sepf =~     Sepal.Length      1.000     Sepal.Width      -0.469   petf =~     Petal.Length      1.000     Petal.Width       0.507   lenf =~     Petal.Length      1.000     Sepal.Length     -0.177   widf =~     Sepal.Width       1.000   strf =~     sepf              1.000     petf              2.084   bulkf =~     lenf              1.000     widf              0.579  Regressions:   strf ~     Species           0.842   bulkf ~     Species           0.290  Covariances:   strf ~~     bulkf             0.065  Variances:     Sepal.Length      0.361     Sepal.Width       0.129     Petal.Length      0.231     Petal.Width       0.047     sepf             -0.120     petf             -0.220     lenf             -0.179     widf              0.084     strf              0.053     bulkf            -0.025 ----------------------------------------------- Warning messages: 1: In lav_data_full(data = data, group = group, group.label = group.label,  :   lavaan WARNING: unordered factor(s) with more than 2 levels detected in data: Species 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 lavaan::lavaan(model = model, data = mydf, model.type = "sem",  :   lavaan WARNING: some estimated variances are negative 4: In lavaan::lavaan(model = model, data = mydf, model.type = "sem",  :   lavaan WARNING: covariance matrix of latent variables is not positive definite; use inspect(fit,"cov.lv") to investigate. 5: In sqrt(ETA2) : NaNs produced 6: In sqrt(ETA2) : NaNs produced 7: In sqrt(ETA2) : NaNs produced >  ``

Do I just take large estimates as signficant? Thanks for your insight.

Contents