Results 1 to 10 of about 526,028 (331)
Intuitionistic Fuzzy Synthetic Measure on the Basis of Survey Responses and Aggregated Ordinal Data [PDF]
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
doaj +2 more sources
Ordinal SuStaIn: Subtype and Stage Inference for Clinical Scores, Visual Ratings, and Other Ordinal Data [PDF]
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
doaj +2 more sources
Towards Ordinal Data Science [PDF]
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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Graphical Models for Ordinal Data. [PDF]
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]
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
openalex +3 more sources
The Assignment of Scores Procedure for Ordinal Categorical Data [PDF]
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
doaj +2 more sources
The Missing Medians: Exclusion of Ordinal Data from Meta-Analyses. [PDF]
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
doaj +2 more sources
Multivariate mixed models accounting for don't know options in ordinal data. [PDF]
Gueorguieva R, Iannario M.
europepmc +2 more sources
PENGOLAHAN DATA BERSKALA ORDINAL
Dalam analisis Multivariat, pengolahan data terkadang mengharuskan data berskala interval / metrik. Apabila data yang dihadapi berskala ordinal, sebaiknya digunakan analisis multivariat nonparametrik. Namun, analisis ini mempunyai banyak kesulitan. Karena software yang mampu mengakomodasi teknik-teknik seperti ini masih kurang.
Euis Sartika
openalex +3 more sources
Biplot 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
doaj +2 more sources

