These names derive from the polychoric and tetrachoric series which are used for estimation of these correlations.
This technique is frequently applied when analysing items on self-report instruments such as personality tests and surveys that often use rating scales with a small number of response options (e.g., strongly disagree to strongly agree).
The smaller the number of response categories, the more a correlation between latent continuous variables will tend to be attenuated.
This aims to reduce the effect of statistical artifacts, such as the number of response scales or skewness of variables leading to items grouping together in factors.
In some disciplines, the statistical technique is rarely applied however, some scholars [1] have demonstrated how it can be used as an alternative to the Pearson correlation.