Results 11 to 20 of about 522,372 (186)

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, Ewa Roszkowska, Marta Kusterka-Jefmańska   +2 more
doaj   +2 more sources

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, Alexandra L. Young, Alexandra L. Young, Jacob W. Vogel, Jacob W. Vogel, Leon M. Aksman, Peter A. Wijeratne, Peter A. Wijeratne, Arman Eshaghi, Arman Eshaghi, Neil P. Oxtoby, Neil P. Oxtoby, Steven C. R. Williams, Daniel C. Alexander, Daniel C. Alexander, for the Alzheimer’s Disease Neuroimaging Initiative   +15 more
doaj   +2 more sources

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, Masanori Shiro, José M. Amigó   +2 more
doaj   +2 more sources

Estimating intracluster correlation for ordinal data. [PDF]

J Appl Stat, 2023
Langworthy BW, Hou Z, Curhan GC, Curhan SG, Wang M.   +4 more
europepmc   +3 more sources

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, Leonid Churilov, Emily S Sena   +2 more
doaj   +2 more sources

Fitting Large Factor Analysis Models With Ordinal Data. [PDF]

Educ Psychol Meas, 2019
DiStefano C, McDaniel HL, Zhang L, Shi D, Jiang Z.   +4 more
europepmc   +3 more sources

Regression analysis of correlated ordinal data using orthogonalized residuals. [PDF]

Biometrics, 2014
Perin J, Preisser JS, Phillips C, Qaqish B.   +3 more
europepmc   +3 more sources

Logistic Biplots for Ordinal Variables Based on Alternating Gradient Descent on the Cumulative Probabilities, with an Application to Survey Data

Algorithms
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, Laura Vicente-González, Elisa Frutos-Bernal, José L. Vicente-Villardón   +3 more
doaj   +2 more sources

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, Dürrschnabel, Dominik, Hanika, Tom   +2 more
doaj   +1 more source

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
doaj   +1 more source