## Get a Relatively Good Model

### Calculate Composites

Go to >>> Analyze menu >>> Data Imputation >>> Regression Imputation

Remember:

- No missing values
- No space in factor names

### Model Construction

Same as SEM.

### Model Fit

Metrics:

```
CMIN --- CMIN/DF: < 3 (good); < 5 (OK)
CMIN --- P: > .05
RMR,GFI --- GFI: >.95
RMR,GFI --- AGFI: >.80
Baseline Comparison --- CFI: >.95 (good); > .90 (OK); > .80 (barely OK)
Parsimony-Adjusted Measure --- PCFI: >.80
RMSEA --- RMSEA: <.05 (good); >.05 && <.10 (OK); >.10 (barely OK)
RMSEA --- PCLOSE: >.05
```

CMIN/DF and P-value together tell you whether you model has a good fit; if the result is not within the range of metrics while you have a big number of sample, it is OK.

### Modification

Go to *Modification Indices* >>> *Covariances* and look for big number of M.I. between each pair of errors. Covariate ONLY those pair of errors at the same level.

For more information, please see Dr. Gaskin's website.