Exploratory Factor Analysis

The table below presents two different tests: the Kaiser-Meyer-Olkin (KMO) Measure of Sampling Adequacy and Bartlett’s test of Sphericity. KMO KMO is a test conducted to examine the strength of the partial correlation (how the factors explain each other) between the variables.

When we talk about communalities, we are interested in the amount of original information contained in each variable that can be extracted from a common factor.

In exploratory factor analysis (EFA) , a scree plot is a plot of eigenvalues of factors arranged in descending order of magnitude from the left to the right side of the plot.

Since a construct/latent variable is measured with multiple items, it is important to find the average of these items particularly when one wishes to conduct a multiple linear regression or maybe look out for the correlation between constructs.

The Fronell-Larcker criterion is one of the most popular techniques used to check the discriminant validity of measurements models.

Your main reason for conducting discriminant validity for your study will be to show how distinct an item or set of items is from others.

Convergent validity is a subset of construct validity. Here, the researcher’s aim is to find out whether the items he claims are measuring a particular construct are indeed measuring them.

Understand the concept of factor loadings and cross loading; steps required to output these results from SPSS.

Download an excel file and calculate your AVE and CR in 5 simple steps!

According to Gefen and Straub (2005), “discriminant validity is shown when each measurement item correlates weakly with another construct excepts for the ones to which it is theoretically associated”.