Results 11 to 20 of about 21,655,635 (191)
Best Practices for Binary and Ordinal Data Analyses. [PDF]
Behav Genet, 2021 Verhulst B, Neale MC.
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Surrogate Data Preserving All the Properties of Ordinal Patterns up to a Certain Length [PDF]
Entropy, 2019 We propose a method for generating surrogate data that preserves all the properties of ordinal patterns up to a certain length, such as the numbers of allowed/forbidden ordinal patterns and transition likelihoods from ordinal patterns into others.
Yoshito Hirata +2 more
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Genomic-Enabled Prediction of Ordinal Data with Bayesian Logistic Ordinal Regression. [PDF]
G3 (Bethesda), 2015 Most genomic-enabled prediction models developed so far assume that the response variable is continuous and normally distributed. The exception is the probit model, developed for ordered categorical phenotypes. In statistical applications, because of the
Montesinos-López OA +4 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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Regression analysis of correlated ordinal data using orthogonalized residuals. [PDF]
Biometrics, 2014 Perin J +3 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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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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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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Methods for Multilevel Ordinal Data in Prevention Research. [PDF]
Prev Sci, 2015 Hedeker D.
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Graphical Models for Ordinal Data. [PDF]
J Comput Graph Stat, 2015 Guo J, Levina E, Michailidis G, Zhu J.
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