An Ordinal I Scaling Method for Questionnaire and Other Ordinal I Data

Modeling Paired Ordinal Response Data

 About 25 years ago, McCullagh proposed a method for modeling univariate ordinal responses. After publishing this paper, other statisticians gradually extended his method, such that we are now able to use more complicated but efficient methods to analyze correlated multivariate ordinal data, and model the relationship between these responses and host of covariates. In this paper, we aim to...

FUZZY NEXUS OVER AN ORDINAL

‎‎In this paper‎, ‎we define fuzzy subnexuses over a nexus $N$‎. ‎Define and study the notions of the prime fuzzy subnexuses and the fractions‎‎induced by them‎. ‎Finally‎, ‎we show that if S is a meet‎‎closed subset of the set Fsub(N), ‎of fuzzy subnexuses of a nexus N‎, ‎and‎‎h= ⋀S ϵ S, ‎then the fractions S^-1 N and h^-1 N are isomorphic as meet-semilattices‎.

Ordinal and Symbolic Data

Classification of Ordinal Data

Predictive learning has traditionally been a standard inductive learning, where different subproblem formulations have been identified. One of the most representative is classification, consisting on the estimation of a mapping from the feature space into a finite class space. Depending on the cardinality of the finite class space we are left with binary or multiclass classification problems. F...

Ordinal longitudinal data analysis

Growth data and longitudinal data in general are often of an ordinal nature. For example, developmental stages may be classified into ordinal categories and behavioral variables repeatedly measured by discrete ordinal scales. Consider the data set presented in Table 15.1. This table contains information on marijuana use taken from five annual waves (1976–80) of the National Youth Survey (Elliot...