Smoothing in ordinal regression: An application to sensory data
The so-called proportional odds assumption is popular in cumulative, ordinal regression. In
practice, however, such an assumption is sometimes too restrictive. For instance, when …
practice, however, such an assumption is sometimes too restrictive. For instance, when …
Robustness of Bayesian ordinal response model against outliers via divergence approach
Ordinal response model is a popular and commonly used regression for ordered categorical
data in a wide range of fields such as medicine and social sciences. However, it is …
data in a wide range of fields such as medicine and social sciences. However, it is …
Bayesian Feature Extraction for Two-Part Latent Variable Model with Polytomous Manifestations
Q Zhang, Y Zhang, Y **a - Mathematics, 2024 - mdpi.com
Semi-continuous data are very common in social sciences and economics. In this paper, a
Bayesian variable selection procedure is developed to assess the influence of observed …
Bayesian variable selection procedure is developed to assess the influence of observed …
Bayesian relative composite quantile regression with ordinal longitudinal data and some case studies
In real applied fields such as clinical medicine, environmental sciences, psychology as well
as economics, we often encounter the task of conducting statistical inference for longitudinal …
as economics, we often encounter the task of conducting statistical inference for longitudinal …
[HTML][HTML] Is Anonymization Through Discretization Reliable? Modeling Latent Probability Distributions for Ordinal Data as a Solution to the Small Sample Size Problem
The growing interest in data privacy and anonymization presents challenges, as traditional
methods such as ordinal discretization often result in information loss by coarsening metric …
methods such as ordinal discretization often result in information loss by coarsening metric …
Bayesian relative composite quantile regression approach of ordinal latent regression model with L1/2 regularization
T Yu‐Zhu, W Chun‐Ho, T Ling‐Nan… - … Analysis and Data …, 2024 - Wiley Online Library
Ordinal data frequently occur in various fields such as knowledge level assessment, credit
rating, clinical disease diagnosis, and psychological evaluation. The classic models …
rating, clinical disease diagnosis, and psychological evaluation. The classic models …
Bayesian joint relatively quantile regression of latent ordinal multivariate linear models with application to multirater agreement analysis
In this paper, we propose a Bayesian quantile regression (QR) approach to jointly model
multivariate ordinal data. Firstly, a multivariate latent variable model is used to link the …
multivariate ordinal data. Firstly, a multivariate latent variable model is used to link the …
Addressing the Impact of Border Enforcement Measures on the Self-Reported Health of Migrants Aiming to Enter Japan During the COVID-19 Epidemic.
J Wels - 2021 - osf.io
Following the spread of COVID-19 in early 2020, Japan has implemented border
enforcement measures to ban most foreigners, including tourists, workers and students from …
enforcement measures to ban most foreigners, including tourists, workers and students from …
[HTML][HTML] Response to Fluvoxamine in the Obsessive-Compulsive Disorder Patients: Bayesian Ordinal Quantile Regression
Background: Obsessive-Compulsive Disorder (OCD) is a chronic neuropsychiatric disorder
associated with unpleasant thoughts or mental images, making the patient repeat physical …
associated with unpleasant thoughts or mental images, making the patient repeat physical …
[書籍][B] Population Stratification Correction in Genetic Association Studies
Z Liu - 2022 - search.proquest.com
In genetic association studies, a major source of confounding in both single nucleotide
polymorphism (SNP) and haplotype studies is the underlying genetic relatedness among the …
polymorphism (SNP) and haplotype studies is the underlying genetic relatedness among the …