Results 281 to 290 of about 534,689 (331)

Answering Ordinal Questions with Ordinal Data Using Ordinal Statistics

Multivariate Behavioral Research, 1996
It is argued that ordinal statistical methods are often more appropriate than their more common counterparts for three types of reasons: Conclusions from them will be unaffected by monotonic transformation of the variables, they are statistically more robust when used appropriately, and they often correspond more closely to the goals of the ...
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Models for Ordinal Agreement Data

Biometrical Journal, 2001
Summary: Statistical models can be used to describe the probabilistic structure underlying cross-classified agreement data. This article explains how models for ordinal agreement data can be understood in terms of an association component and an agreement component.
Schuster, Christof, von Eye, Alexander
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Inequality with Ordinal Data

Economica, 2017
The standard theory of inequality measurement assumes that the equalisand is a cardinal quantity, with known cardinalization. However, one often needs to make inequality comparisons where either the cardinalization is unknown or the underlying data are categorical.
Cowell, Frank, Flachaire, Emmanuel
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On the Contextual Logic of Ordinal Data

2000
This paper reports on first attempts to develop a contextual logic of ordinal data. The investigations are based on a mathematical theory of ordinal contexts which has been developed within Formal Concept Analysis. From ordinal contexts, binary power context families are derived as semantic basis of a contextual logic of ordinal data.
Silke Pollandt, Rudolf Wille
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Consistency in ordinal data analysis I

Mathematical Social Sciences, 2002
The aim of this paper to solve the problem of characterizing independently of any particular field of data analysis, i.e., cluster analysis, factor analysis etc., reduction methods that satisfy the modest reduction requirement in case that the data are measured in a scale that is not necessarily rational.
Gerhard Herden, Andreas Pallack
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Ordinal Data: An Alternative Distribution

Psychometrika, 1979
To date, virtually all techniques appropriate for ordinal data are based on the uniform probability distribution over the permutations. In this paper we introduce and examine an alternative probability model for the distribution of ordinal data. Preliminary to deriving the expectations of Spearman's rho and Kendall's tau under this model, we show how ...
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Learning ordinal data

WIREs Computational Statistics, 2015
Classification is an important topic in statistical learning. The goal of classification is to build a predictive model from the training dataset for the class label of an observation. It is commonly assumed that the class labels are unordered. However, in many real applications, there exists an intrinsic ordinal relation between the class labels ...
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Mining Ordinal Patterns For Data Cleaning

Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration, 2004. IRI 2004., 2005
It is well recognized that sequential pattern mining plays an essential role in many scientific and business domains. In this paper, a new extension of sequential pattern, ordinal pattern, is proposed. An ordinal pattern is an ordinal sequence of attributes, whose values commonly occur in ascending order over data set.
Ya-Bo Liu, Dayou Liu
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On the Use of Ordinal Data in Data Envelopment Analysis

Journal of the Operational Research Society, 1993
Summary: In many problems involving efficiency analysis using DEA, certain factors may be measurable only on an ordinal scale. Specifically, it may be possible only to rank order the DMUs according to a factor, rather than being able to assign a specific numerical value of that factor to each DMU.
Cook, Wade D., Kress, Moshe, Seiford, Lawrence M.   +2 more
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The Ordination of Incidence Data

The Journal of Ecology, 1978
SUMMARY (1) Principal components analysis of incidence (presence and absence) data produces a horseshoe effect. A new method, called step-across, is described which removes this effect. (2) From a matrix of joint occurrences, distances are found directly for all positive values.
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