Model Assessment

Pemodelan Persamaan Struktural dengan lavaan di R

Erin Buchanan

Professor

Standardized Loadings

summary(visual.fit, standardized = TRUE)

Latent Variables:
           Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
  visual =~                                                             
    x1        1.000                               0.621    0.533
    x2        0.586    0.139    4.215    0.000    0.364    0.310
    x3        0.882    0.149    5.923    0.000    0.548    0.485
    x7        0.728    0.137    5.320    0.000    0.452    0.416
    x8        0.944    0.143    6.599    0.000    0.586    0.580
    x9        1.205    0.170    7.095    0.000    0.748    0.742

Fit Indices

Model Fit - how well the data fit the specified model
- Goodness of fit indices like the Comparative Fit Index (CFI) or the Tucker Lewis Index (TLI)
- Badness of fit indices like Root Mean Square Error of Approximation (RMSEA) or Standardized Root Mean Square Residual (SRMR)
Measuring Model Fit

Fit Indices

summary(visual.fit, standardized = TRUE, 
        fit.measures = TRUE)

User model versus baseline model:
  Comparative Fit Index (CFI)                    0.701
  Tucker-Lewis Index (TLI)                       0.502
                        _ _ _
Root Mean Square Error of Approximation:
  RMSEA                                          0.190
                        _ _ _
Standardized Root Mean Square Residual:
  SRMR                                           0.111

Let's practice!

Pemodelan Persamaan Struktural dengan lavaan di R