Very Simple Structure: An Alternative Procedure For Estimating The Optimal Number Of Interpretable Factors

A new procedure for determining the optimal number of interpretable factors to extract from a correlation matrix is introduced and compared to more conventional procedures.

Abstract

A new procedure for determining the optimal number of interpretable factors to extract from a correlation matrix is introduced and compared to more conventional procedures. The new method evaluates the magnitude of the Very Simple Structure index of goodness of fit for factor solutions of increasing rank. The number of factors which maximizes the VSS criterion is taken as being the optimal number of factors to extract. Thirty-two artificial and two real data sets are used in order to compare this procedure with such methods as maximum likelihood, the eigenvalue greater than 1.0 rule, and comparison of the observed eigenvalues with those expected from random data.