The incremental value of Rank Factor Analysis (MRFA)

MRFA is a method of exploratory factor analysis, which minimizes the common variance that is left unexplained with any given number of factors. Compared to all previous methods of exploratory factor analysis, MRFA has two outstanding features: It is fully protected against so-called improper solutions, and it permits evaluating the percentages of explained and unexplained common variance. Although the method seems attractive, a thorough investigation of its theoretical properties and its practical value is still needed. Key questions are: 1. Under what conditions (number of factors, type of variables) is the solution unique ? 2. What sample sizes are needed to get reliable results from MRFA ?3. How does the method behave, compared with Maximum Likelihood Factor Analysis and Iterative Principal Factor Analysis (based on least-squares estimation) in terms of recovering the underlying factor structure ? A specific point to be clarified is the relation between the percentage of common variance explained with MRFA and the measures of fit obtained with MLFA and IPFA.