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
doaj +3 more sources
Fitting Large Factor Analysis Models With Ordinal Data. [PDF]
Educ Psychol Meas, 2019 A simulation study was conducted to investigate the model size effect when confirmatory factor analysis (CFA) models include many ordinal items. CFA models including between 15 and 120 ordinal items were analyzed with mean- and variance-adjusted weighted
DiStefano C +4 more
europepmc +4 more sources
Polychoric Correlation With Ordinal Data in Nursing Research. [PDF]
Nurs Res, 2022 Background Measures in nursing research frequently use Likert scales that yield ordinal data. Confirmatory factor analysis using Pearson correlations commonly applies to such data, although this violates ordinal scale assumptions.
Kiwanuka F +4 more
europepmc +2 more sources
Factor Retention Using Machine Learning With Ordinal Data. [PDF]
Appl Psychol Meas, 2022 Determining the number of factors in exploratory factor analysis is probably the most crucial decision when conducting the analysis as it clearly influences the meaningfulness of the results (i.e., factorial validity).
Goretzko D, Bühner M.
europepmc +2 more sources
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
doaj +2 more sources
Inequality Comparisons with Ordinal Data [PDF]
The Review of Income and Wealth, 2020 Non-intersection of appropriately-defined Generalized Lorenz (GL) curves is equivalent to a unanimous ranking of distributions of ordinal data by all Cowell and Flachaire (Economica 2017) indices of inequality and by a new index based on GL curve areas ...
Stephen P. Jenkins
openalex +2 more sources
Comparison of cronbach’s alpha and McDonald’s omega for ordinal data: Are they different?
International Journal of Assessment Tools in Education, 2023 Among all, Cronbach’s Alpha and McDonald’s Omega are commonly used for reliability estimations. The alpha uses inter-item correlations while omega is based on a factor analysis result. This study uses simulated ordinal data sets to test whether the alpha
Fatih Orçan
openalex +3 more sources
The Swedish RAND-36 Health Survey - reliability and responsiveness assessed in patient populations using Svensson's method for paired ordinal data. [PDF]
J Patient Rep Outcomes, 2017 BackgroundThe Short Form 36-Item Survey is one of the most commonly used instruments for assessing health-related quality of life. Two identical versions of the original instrument are currently available: the public domain, license free RAND-36 and the ...
Orwelius L +8 more
europepmc +2 more sources
Optimizing the maximum reported cluster size in the spatial scan statistic for ordinal data. [PDF]
PLoS One, 2017 The spatial scan statistic is an important tool for spatial cluster detection. There have been numerous studies on scanning window shapes. However, little research has been done on the maximum scanning window size or maximum reported cluster size ...
Kim S, Jung I.
europepmc +2 more sources
Estimating intracluster correlation for ordinal data. [PDF]
J Appl Stat, 2023 Langworthy BW +4 more
europepmc +3 more sources