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Ordinal regression

About: Ordinal regression is a research topic. Over the lifetime, 1879 publications have been published within this topic receiving 65431 citations.


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Journal ArticleDOI
TL;DR: Two possible formulations of the level dependent Choquet integral are presented where importance and interaction of criteria are constant inside each one of the subintervals in which the interval of evaluations for considered criteria is split or vary with continuity inside the whole intervals of evaluations.

22 citations

Posted Content
TL;DR: In this article, an equivalence between three incomplete rankings of distributions of an ordinally measurable attribute is established, which are associated with the possibility of going from distribution to the other by a finite sequence of two elementary operations: increments of the attribute and the so-called Hammond transfer.
Abstract: This paper establishes an equivalence between three incomplete rankings of distributions of an ordinally measurable attribute. The first ranking is that associated with the possibility of going from distribution to the other by a finite sequence of two elementary operations: increments of the attribute and the so-called Hammond transfer. The later transfer is like the Pigou-Dalton transfer, but without the requirement - that would be senseless in an ordinal setting - that the "amount" transferred from the "rich" to the "poor" is fixed. The second ranking is an easy-to-use statistical criterion associated to a specifically weighted recursion on the cumulative density of the distribution function. The third ranking is that resulting from the comparison of numerical values assigned to distributions by a large class of additively separable social evaluation functions. Illustrations of the criteria are also provided.

22 citations

Journal ArticleDOI
TL;DR: Simulation studies comparing the performance of the different diagnostic methods indicate that some of the graphical methods are more powerful in detecting model misspecification than the Hosmer-Lemeshow-type goodness-of-fit statistics for the class of models studied.
Abstract: The cumulative logit or the proportional odds regression model is commonly used to study covariate effects on ordinal responses. This paper provides some graphical and numerical methods for checking the adequacy of the proportional odds regression model. The methods focus on evaluating functional misspecification for specific covariate effects, but misspecification of the link function can also be dealt with under the same framework. For the logistic regression model with binary responses, Arbogast and Lin (Statist. Med. 2005; 24:229-247) developed similar graphical and numerical methods for assessing the adequacy of the model using the cumulative sums of residuals. The paper generalizes their methods to ordinal responses and illustrates them using an example from the VA Normative Aging Study. Simulation studies comparing the performance of the different diagnostic methods indicate that some of the graphical methods are more powerful in detecting model misspecification than the Hosmer-Lemeshow-type goodness-of-fit statistics for the class of models studied.

22 citations

Journal ArticleDOI
TL;DR: In this paper, the authors examined the influences on individual happiness using ordinal logistic regression and chi-square analyses, and found that an individual's education, gender, age distribution and work environment are influential in producing higher levels of happiness.
Abstract: Globally, individuals seek happiness, but not everybody is happy. Economic reasoning suggests that rising incomes with expansions in GDP enhance the quality of life and subjective well-being. This paper examines the influences on individual happiness, using ordinal logistic regression and chi-square analyses. Based on the findings of a small case study, the chi-square test indicated that a significant relationship exists between gender, education, ethnicity, children, marital status, employment relations, income and self-reported happiness. The study also found that, on average, happier people tended to be educated, married with children, and treated fairly at work. But having too many children produced a decrement in individual happiness. The ordinal regression results indicate that an individual’s education, gender, age distribution and work environment are influential in producing higher levels of happiness. Entrepreneurs were found to have a significantly higher mean level of happiness than employees. In the workplace, individuals who experienced personal growth and were able to contribute their ideas tended to be happier, relative to others who perceived themselves to be ‘restricted’.

22 citations

01 Jan 2010
TL;DR: In this paper, C. Reading et al. present a multilevel model for ORDINAL RESPONSE data for teaching statistics education in the context of data and context in statistics education.
Abstract: In C. Reading (Ed.), Data and context in statistics education: Towards an evidence-based society. Proceedings of the Eighth International Conference on Teaching Statistics (ICOTS8, July, 2010), Ljubljana, Slovenia. Voorburg, The Netherlands: International Statistical Institute. www.stat.auckland.ac.nz/~iase/publications.php [© 2010 ISI/IASE] AN ILLUSTRATION OF MULTILEVEL MODELS FOR ORDINAL RESPONSE DATA

22 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023102
2022191
202188
202093
201979
201873