Parallel analysis has been well documented to be an effective and accurate method for determining the number of factors to retain in exploratory factor analysis. Despite its theoretical and empirical advantages, the popularity of parallel analysis has been thwarted by its limited access in statistical software such as SPSS and SAS, especially in software that analyzes ordinal data. Among the few commonly used procedures, the Hayton, Allen, and Scarpello (2004) procedure requires manually computing the mean of eigenvalues from at least 50 replications.