Contents
What is invariance test in CFA?
Measurement invariance or measurement equivalence is a statistical property of measurement that indicates that the same construct is being measured across some specified groups. Measurement invariance is often tested in the framework of multiple-group confirmatory factor analysis (CFA).
What is multigroup confirmatory factor analysis?
Multigroup confirmatory factor analysis (MCFA) is a popular method for the examination of measurement invariance and specifically, factor invariance. This simulation study examines these methods in terms of accuracy (i.e., true positive and false positive rates) of identifying invariant referent variables.
How to test for measurement invariance in CFA?
As with a typical CFA, you start by specifying the relationships between each item in the measure you’re using and the latent factor (s) that the items are stipulated to measure. Take, for example, the five-item Satisfaction with Life Scale (Diener, Emmons, Larsen & Griffin, 1985).
How to test for configural invariance in a model?
To test configural invariance, you fit the model you have specified onto each of the age groups, leaving all factor loadings and item intercepts free to vary for each group. You then compare model fit across all age groups — a good multi-group model fit suggests that the overall factor structure holds up similarly for all ages.
Which is the best way to test measurement invariance?
Measurement invariance is something you can’t assume. You have to test it. There are two methods for testing for measurement invariance: multiple group analysis, and a simpler approach known as CFA with covariates. In this article we will focus on measurement invariance using multiple group analysis.
How to test group invariance with confirmatory factor?
Before we show how you can analyze this via tests of group invariance using confirmatory factor analysis, let’s consider some other methods that you might use. Exploratory Factor Analysis – You might try running an exploratory factor analysis for the graduate students and a separate exploratory factor analysis for the faculty members.