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In the last two decade, it has become clear that retention methods must utilize polychoric correlation instead of Pearson correlation to eliminate drawbacks such as underestimation of the magnitude of the relationship between latent variables that result in spurious findings (Bernstein & Teng, 1989). In the present study, the literature review will be examined and compared using Monte Carlo simulation to determine the most parsimonious method of retention for categorical data. With continuous variables, the majority of researchers still implement Cattell’s scree test (Henson & Roberts, 2006) and Kaiser-Guttman-1 rule (Velicer et al., 2000), because these procedures are the default in popular statistical packages, such as SPSS and SAS. The present study will examine two of the most accurate methods: MAP (Minimum Average Partial) and PA (Parallel Analysis) along with Very Simple Structure (VSS) with categorical variables.