Results 31 to 40 of about 5,782,543 (332)
Multiple Ordinal Correlation Based on Kendall’s Tau Measure: A Proposal
Mathematics, 2021 The joint analysis of various ordinal variables is necessary in many experimental studies within research fields such as sociology and psychology. Therefore, the necessary measures of multiple ordinal dependence must be easy to interpret and facilitate ...
Juan M. Muñoz-Pichardo +3 more
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AXIOMATIC DETERMINATION OF A CLASS OF ORDINAL VARIATION MEASURES
Studies in Logic, Grammar and Rhetoric, 2017 The article deals with the problem of the dispersion of ordinal variables. At first, it specifies the very concept of dispersion for this type of scale. Then some of the most known measures that fit to the concept of ordinal variation are recalled.
Kęska Adam
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Bayesian test of independence and conditional independence of two ordinal variables [PDF]
Journal of Statistical Theory and Applications (JSTA), 2015 For analysis of contingency tables with large sample size, classical approaches using approximate methods have high power. However, when the sample size is small or some cells have frequencies less than 5, classical approaches are so conservative.
Zahra Saberi, Mojtab Ganjali
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Multinomial and ordinal Logistic regression analyses with multi-categorical variables using R
Annals of Translational Medicine, 2020 Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai 200032, China Correspondence to: Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai 200032, China.
Jiaqi Liang, Guoshu Bi, C. Zhan
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A new correlation coefficient between categorical, ordinal and interval variables with Pearson characteristics [PDF]
Computational Statistics & Data Analysis, 2018 A prescription is presented for a new and practical correlation coefficient, $\phi_K$, based on several refinements to Pearson's hypothesis test of independence of two variables.
M. Baak +4 more
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Measuring risk with ordinal variables [PDF]
The Journal of Operational Risk, 2013 In this paper we propose a novel approach for measuring risks when the data available is expressed on an ordinal scale. As a result we obtain a new index of riskboundedbetween 0and 1,whichleadstoariskorderingthatisconsistentwith a stochastic dominance approach. The proposed measure, being nonparametric, can be applied to a wide range of problems, where
Silvia Figini, Paolo Giudici
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Clustering large mixed-type data with ordinal variables
Advances in Data Analysis and ClassificationOne of the most frequently used algorithms for clustering data with both numeric and categorical variables is the k-prototypes algorithm, an extension of the well-known k-means clustering.
G. Szepannek +2 more
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How Much Does the Cardinal Treatment of Ordinal Variables Matter? An Empirical Investigation
Political Analysis, 2018 Many researchers use an ordinal scale to quantitatively measure and analyze concepts. Theoretically valid empirical estimates are robust in sign to any monotonic increasing transformation of the ordinal scale.
J. Bloem
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Journal of Computational And Graphical Statistics, 2020 This article is about the co-clustering of ordinal data. Such data are very common on e-commerce platforms where customers rank the products/services they bought.
Marco Corneli, C. Bouveyron, P. Latouche
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Adaptive Sparse Clustering of Mixed Data Using Azzalini-Encoded Ordinal Variables
AxiomsIn this paper, we propose a novel sparse clustering method designed for high-dimensional mixed-type data, integrating Azzalini’s score-based encoding for ordinal variables. Our approach aims to retain the inherent nature of each variable type—continuous,
Ismail Arjdal +3 more
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