Results 1 to 10 of about 534,590 (232)
Towards Ordinal Data Science [PDF]
Transactions on Graph Data and Knowledge, 2023 Order is one of the main instruments to measure the relationship between objects in (empirical) data. However, compared to methods that use numerical properties of objects, the amount of ordinal methods developed is rather small.
Stumme, Gerd +2 more
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Intuitionistic Fuzzy Synthetic Measure on the Basis of Survey Responses and Aggregated Ordinal Data [PDF]
Entropy, 2021 The paper addresses the problem of complex socio-economic phenomena assessment using questionnaire surveys. The data are represented on an ordinal scale; the object assessments may contain positive, negative, no answers, a “difficult to say” or “no ...
Bartłomiej Jefmański +2 more
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Ordinal SuStaIn: Subtype and Stage Inference for Clinical Scores, Visual Ratings, and Other Ordinal Data [PDF]
Frontiers in Artificial Intelligence, 2021 Subtype and Stage Inference (SuStaIn) is an unsupervised learning algorithm that uniquely enables the identification of subgroups of individuals with distinct pseudo-temporal disease progression patterns from cross-sectional datasets.
Alexandra L. Young +15 more
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Graphical Models for Ordinal Data. [PDF]
J Comput Graph Stat, 2015 A graphical model for ordinal variables is considered, where it is assumed that the data are generated by discretizing the marginal distributions of a latent multivariate Gaussian distribution. The relationships between these ordinal variables are then described by the underlying Gaussian graphical model and can be inferred by estimating the ...
Guo J, Levina E, Michailidis G, Zhu J.
europepmc +4 more sources
Classification of Ordinal Data [PDF]
CoRR, 2006 Classification of ordinal data is one of the most important tasks of relation learning. In this thesis a novel framework for ordered classes is proposed. The technique reduces the problem of classifying ordered classes to the standard two-class problem. The introduced method is then mapped into support vector machines and neural networks. Compared with
Jaime S. Cardoso
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The Missing Medians: Exclusion of Ordinal Data from Meta-Analyses. [PDF]
PLoS ONE, 2015 BackgroundMeta-analyses are considered the gold standard of evidence-based health care, and are used to guide clinical decisions and health policy. A major limitation of current meta-analysis techniques is their inability to pool ordinal data.
Toby B Cumming +2 more
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The Assignment of Scores Procedure for Ordinal Categorical Data [PDF]
The Scientific World Journal, 2014 Ordinal data are the most frequently encountered type of data in the social sciences. Many statistical methods can be used to process such data. One common method is to assign scores to the data, convert them into interval data, and further perform ...
Han-Ching Chen, Nae-Sheng Wang
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Multivariate mixed models accounting for don't know options in ordinal data. [PDF]
J R Stat Soc Ser A Stat SocGueorguieva R, Iannario M.
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AlgorithmsBiplot methods provide a framework for the simultaneous graphical representation of both rows and columns of a data matrix. Classical biplots were originally developed for continuous data in conjunction with principal component analysis (PCA).
Julio C. Hernández-Sánchez +3 more
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Drawbacks of Normalization by Percentile Ranks in Citation Impact Studies [PDF]
Journal of Library and Information Studies, 2022 This paper discusses drawbacks of the percentile rank method for citation impact normalization which have hitherto been neglected in the bibliometrics literature.
Paul Donner
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