Results 21 to 30 of about 526,028 (331)

Modelling Qualitative Data from Repeated Surveys

Computation, 2023
This article presents an innovative dynamic model that describes the probability distributions of ordered categorical variables observed over time. For this purpose, we extend the definition of the mixture distribution obtained from the combination of a ...
Marcella Corduas, Domenico Piccolo
doaj   +1 more source

Conditional entropy of ordinal patterns [PDF]

, 2014
In this paper we investigate a quantity called conditional entropy of ordinal patterns, akin to the permutation entropy. The conditional entropy of ordinal patterns describes the average diversity of the ordinal patterns succeeding a given ordinal ...
Keller, Karsten, Unakafov, Anton M.
core   +1 more source

Interlaboratory comparison of the intensity of drinking water odor and taste by two-way ordinal analysis of variation without replication

Journal of Water and Health, 2022
A case study of ordinal data from human organoleptic examination (sensory analysis) of drinking water obtained in an interlaboratory comparison of 49 ecological laboratories is described.
Tamar Gadrich, Ilya Kuselman, Francesca R. Pennecchi, D. Brynn Hibbert, Anastasia A. Semenova, Pui Sze Cheow, Vladimir N. Naidenko   +6 more
doaj   +1 more source

Goodness-of-Fit and Generalized Estimating Equation Methods for Ordinal Responses Based on the Stereotype Model

Stats, 2022
Background: Data with ordinal categories occur in many diverse areas, but methodologies for modeling ordinal data lag severely behind equivalent methodologies for continuous data.
Daniel Fernández, Louise McMillan, Richard Arnold, Martin Spiess, Ivy Liu   +4 more
doaj   +1 more source

Using rank data to estimate health state utility models [PDF]

, 2006
In this paper we report the estimation of conditional logistic regression models for the Health Utilities Index Mark 2 and the SF-6D, using ordinal preference data.
Aki Tsuchiya, Anthony O’Hagan, Brazier, Brazier, Broome, Cairns, Christopher McCabe, Currim, Dolan, Dyer, Hausman, Jennifer Roberts, John Brazier, Katherine Stevens, Kind, Koop, Ljung, Lloyd, McFadden, Peter Gilks, Saigal, Thurstone, Torrance, Torrance, Torrance   +24 more
core   +1 more source

Comparison Non-Parametric Machine Learning Algorithms for Prediction of Employee Talent

IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2021
Classification of ordinal data is part of categorical data. Ordinal data consists of features with values based on order or ranking. The use of machine learning methods in Human Resources Management is intended to support decision-making based on ...
I Ketut Adi Wirayasa, Arko Djajadi, H andri Santoso, Eko Indrajit   +3 more
doaj   +1 more source

A Measure of Departure from Average Marginal Homogeneity for Square Contingency Tables with Ordered Categories

Revstat Statistical Journal, 2011
For the analysis of square contingency tables, Tomizawa, Miyamoto and Ashihara (2003) considered a measure to represent the degree of departure from marginal homogeneity.
Kouji Yamamoto , Shuji Ando , Sadao Tomizawa   +2 more
doaj   +1 more source

Bayesian analysis of Ecological Momentary Assessment (EMA) data collected in adults before and after hearing rehabilitation

Frontiers in Digital Health, 2023
This paper presents a new Bayesian method for analyzing Ecological Momentary Assessment (EMA) data and applies this method in a re-analysis of data from a previous EMA study.
Arne Leijon, Petra von Gablenz, Inga Holube, Jalil Taghia, Karolina Smeds   +4 more
doaj   +1 more source

Testing Measurement Invariance with Ordinal Missing Data: A Comparison of Estimators and Missing Data Techniques [PDF]

, 2019
Ordinal missing data are common in measurement equivalence/invariance (ME/I) testing studies. However, there is a lack of guidance on the appropriate method to deal with ordinal missing data in ME/I testing.
Chen, Po-Yi, Garnier-Villarreal, Mauricio, Jia, Fan, Kite, Benjamin Arthur, Wu, Wei   +4 more
core   +2 more sources

Multimodal Affect Models: An Investigation of Relative Salience of Audio and Visual Cues for Emotion Prediction

Frontiers in Computer Science, 2021
People perceive emotions via multiple cues, predominantly speech and visual cues, and a number of emotion recognition systems utilize both audio and visual cues.
Jingyao Wu, Ting Dang, Ting Dang, Vidhyasaharan Sethu, Eliathamby Ambikairajah   +4 more
doaj   +1 more source