| Literature DB >> 35706886 |
Abstract
Skewness is a well-established statistical concept for continuous and, to a lesser extent, for discrete quantitative statistical variables. However, for ordered categorical variables, limited literature concerning skewness exists, although this type of variables is common for behavioral, educational, and social sciences. Suitable measures of skewness for ordered categorical variables have to be invariant with respect to the group of strictly increasing, continuous transformations. Therefore, they have to depend on the corresponding maximal-invariants. Based on these maximal-invariants, we propose a new class of skewness functionals, show that members of this class preserve a suitable ordering of skewness and derive the asymptotic distribution of the corresponding skewness statistic. Finally, we show the good power behavior of the corresponding skewness tests and illustrate these tests by applying real data examples.Entities:
Keywords: 62; Ordered categorical variables; maximal invariants; skewness analysis; skewness ordering
Year: 2020 PMID: 35706886 PMCID: PMC9041824 DOI: 10.1080/02664763.2020.1757045
Source DB: PubMed Journal: J Appl Stat ISSN: 0266-4763 Impact factor: 1.416