Topic
Ordinal regression
About: Ordinal regression is a research topic. Over the lifetime, 1879 publications have been published within this topic receiving 65431 citations.
Papers published on a yearly basis
Papers
More filters
TL;DR: The ordinal regression model with Clog-log is a better fit in determination of significant factors associated with periodontal disease as compared to models with logit, probit and nlog-log built-in link functions.
Abstract: Aim: The study aimed to determine the factors associated with periodontal disease (different levels of severity) by using different regression models for ordinal data. Design: A cross-sectional design was employed using clinical examination and 'questionnaire with interview' method. Materials and Methods: The study was conducted during June 2008 to October 2008 in Dharwad, Karnataka, India. It involved a systematic random sample of 1760 individuals aged 18-40 years. The periodontal disease examination was conducted by using Community Periodontal Index for Treatment Needs (CPITN). Statistical Analysis Used: Regression models for ordinal data with different built-in link functions were used in determination of factors associated with periodontal disease. Results: The study findings indicated that, the ordinal regression models with four built-in link functions (logit, probit, Clog-log and nlog-log) displayed similar results with negligible differences in significant factors associated with periodontal disease. The factors such as religion, caste, sources of drinking water, Timings for sweet consumption, Timings for cleaning or brushing the teeth and materials used for brushing teeth were significantly associated with periodontal disease in all ordinal models. Conclusions: The ordinal regression model with Clog-log is a better fit in determination of significant factors associated with periodontal disease as compared to models with logit, probit and nlog-log built-in link functions. The factors such as caste and time for sweet consumption are negatively associated with periodontal disease. But religion, sources of drinking water, Timings for cleaning or brushing the teeth and materials used for brushing teeth are significantly and positively associated with periodontal disease.
11 citations
TL;DR: In this article, a new type of scale, called the bipolar ordinal scale, was defined with assumptions slightly stronger than those of the normal ordinal scales, and a similarity index, called r BP, is defined between persons with scores on this scale.
Abstract: A new type of scale, called the bipolar ordinal scale, is defined with assumptions slightly stronger than those of the normal ordinal scale. A similarity index, called r BP, is defined between persons with scores on this scale. It is invariant over item reflection. It is also an E-correlation coefficient and can thus be used in a Q-analysis.
11 citations
TL;DR: In this article, the distribution of functionals of discrete ordinal variables is studied and the probability mass functions of several summary measures and of two important L -estimators that can be profitably used in data analysis.
11 citations
Posted Content•
TL;DR: In this article, a new multiple criteria decision-aiding method is proposed to deal with sorting problems in which alternatives are evaluated on criteria structured in a hierarchical way and presenting interactions.
Abstract: In this paper we propose a new multiple criteria decision aiding method to deal with sorting problems in which alternatives are evaluated on criteria structured in a hierarchical way and presenting interactions. The underlying preference model of the proposed method is the Choquet integral, while the hierarchical structure of the criteria is taken into account by applying the Multiple Criteria Hierarchy Process. Considering the Choquet integral based on a 2-additive capacity, the paper presents a procedure to find all the minimal sets of pairs of interacting criteria representing the preference information provided by the Decision Maker (DM). Robustness concerns are also taken into account by applying the Robust Ordinal Regression and the Stochastic Multicriteria Acceptability Analysis. Even if in different ways, both of them provide recommendations on the hierarchical sorting problem at hand by exploring the whole set of capacities compatible with the preferences provided by the DM avoiding to take into account only one of them. The applicability of the considered method to real world problems is demonstrated by means of an example regarding rating of European Countries by considering economic and financial data provided by Standard \& Poor's Global Inc.
11 citations
09 Oct 2006
TL;DR: This paper presents and verifies an alternative approach to the quantitative and ordinal association rule mining that applies simple arithmetic operations in order to construct the cedents and searches for areas of increased association which are finally decomposed into conjunctions of literals.
Abstract: Association rules have exhibited an excellent ability to identify interesting association relationships among a set of binary variables describing huge amount of transactions. Although the rules can be relatively easily generalized to other variable types, the generalization can result in a computationally expensive algorithm generating a prohibitive number of redundant rules of little significance. This danger especially applies to quantitative and ordinal variables. This paper presents and verifies an alternative approach to the quantitative and ordinal association rule mining. In this approach, quantitative or ordinal variables are not immediately transformed into a set of binary variables. Instead, it applies simple arithmetic operations in order to construct the cedents and searches for areas of increased association which are finally decomposed into conjunctions of literals. This scenario outputs rules that do not syntactically differentiate from classical association rules.
11 citations