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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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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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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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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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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Using the weighted Kendall Distance to analyze rank data in psychology [PDF]
Tutorials in Quantitative Methods for Psychology, 2021 Although the Kendall distance is a standard metric in computer science, it is less widely used in psychology. We demonstrate the usefulness of the Kendall distance for analyzing psychological data that take the form of ranks, lists, or orders of items ...
van Doorn, Johnny +2 more
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ORDINAL LOGISTIC REGRESSION MODEL AND CLASSIFICATION TREE ON ORDINAL RESPONSE DATA
Barekeng, 2022 Logistic regression (LR) is a model that associates the relationship between category-type response variables with quantitative or quantitative and qualitative predictor variables. The prediction of the LR model is in the form of probability.
Jajang Jajang +2 more
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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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Bivariate Distributions Underlying Responses to Ordinal Variables
Psych, 2021 The association between two ordinal variables can be expressed with a polychoric correlation coefficient. This coefficient is conventionally based on the assumption that responses to ordinal variables are generated by two underlying continuous latent ...
Laura Kolbe, Frans Oort, Suzanne Jak
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Model-Assisted and Model-Calibrated Estimation for Class Frequencies with Ordinal Outcomes
Revstat Statistical Journal, 2022 This paper considers new techniques for complex surveys in the case of estimation of proportions when the variable of interest has ordinal outcomes. Ordinal modelassisted and ordinal model-calibrated estimators are introduced for class frequencies in a ...
Maria del Mar Rueda +3 more
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