It is named after psychologist John L. Horn, who created the method, publishing it in the journal Psychometrika in 1965.
[2] Parallel analysis is regarded as one of the more accurate methods for determining the number of factors or components to retain.
In particular, unlike early approaches to dimensionality estimation (such as examining scree plots), paralell analysis has the virtue of an objective decision criterion.
[4][5] Other methods of determining the number of factors or components to retain in an analysis include the scree plot, Kaiser rule, or Velicer's MAP test.
[6] Anton Formann provided both theoretical and empirical evidence that parallel analysis's application might not be appropriate in many cases since its performance is influenced by sample size, item discrimination, and type of correlation coefficient.