# What is Congeneric model?

## What is Congeneric model?

The congeneric model assumes that each item’s true score is a linear combination of a common factor ( ) (i.e., ). is often referred to as a factor loading of item . is the sum of all the elements of the fitted/implied covariance matrix of obtained from estimates of ‘s and. ‘s.

**What is measurement model in CFA?**

CFA is distinguished from structural equation modeling by the fact that in CFA, there are no directed arrows between latent factors. In the context of SEM, the CFA is often called ‘the measurement model’, while the relations between the latent variables (with directed arrows) are called ‘the structural model’.

### What is tau equivalent model?

The tau-equivalent measurement model requires items to measure the same latent construct using the same scale; that is, the path coefficients from the latent factor to the measured items are constrained to equality.

**How do you do a confirmatory factor analysis?**

Steps in a Confirmatory Factor Analysis. The first step is to calculate the factor loadings of the indicators (observed variables) that make up the latent construct. The standardized factor loading squared is the estimate of the amount of the variance of the indicator that is accounted for by the latent construct.

#### Which is the most fundamental model in CFA?

The most fundamental model in CFA is the one factor model, which will assume that the covariance (or correlation) among items is due to a single common factor. Much like exploratory common factor analysis, we will assume that total variance can be partitioned into common and unique variance.

**Which is better two factor Cfa or uncorrelated CFA?**

We can see that the uncorrelated two factor CFA solution gives us a higher chi-square (lower is better), higher RMSEA and lower CFI/TLI, which means overall it’s a poorer fitting model. We talk to the Principal Investigator and decide to go with a correlated (oblique) two factor model.

## What is the difference between RMSEA and CFI?

CFI is the confirmatory factor index – values can range between 0 and 1 (values greater than 0.90, conservatively 0.95 indicate good fit) RMSEA is the root mean square error of approximation (values of 0.01, 0.05 and 0.08 indicate excellent, good and mediocre fit respectively, some go up to 0.10 for mediocre).

**What are the three main factor indices in CFA?**

The three main model fit indices in CFA are: CFI is the confirmatory factor index – values can range between 0 and 1 (values greater than 0.90, conservatively 0.95 indicate good fit) RMSEA is the root mean square error of approximation (values of 0.1, 0.05 and 0.08 indicate excellent, good and mediocre fit, some go up to 0.10 for mediocre).