ArticleJournal of statistical software2021
Regularized Ordinal Regression and the ordinalNet R Package.
Article in Journal of statistical software, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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Who cites it
36 citing papers in PubMed.
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- DEVELOPMENT AND APPLICATION OF BRAIN TISSUE BASED MULTI-OMICS PROFILE SCORES FOR ALZHEIMER'S DISEASE.Research square · 2026Article
- Emotion-specific regulation components differentially predict profiles of adolescent psychosocial dysfunction.Scientific reports · 2026Article
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- Mapping between EQ-5D-5L and EQ-5D-3L in lumbar spine surgery patients: Machine learning compared to crosswalk algorithms.Brain & spine · 2026Article
- Career Intentions in Academic Medicine: Factors Influencing Pursuit and Gender Disparities.Advances in medical education and practice · 2026Article
- Visual detection of seizures in mice using supervised machine learning.Cell reports methods · 2025Article
- Identifying correlates of viral rebound timing and viral control in SHIV-infected infant macaques after ART interruption.Science translational medicine · 2025Article
- Understanding resilience in medical interns through ecological momentary assessments, predictive modelling, and topic analysis.Communications medicine · 2025Article
- Comparing the predictive discrimination of machine learning models for ordinal outcomes: A case study of dehydration prediction in patients with acute diarrhea.PLOS digital health · 2025Article
- Transcriptomic Biomarkers Associated With Microbiological Etiology and Disease Severity in Childhood Pneumonia.The Journal of infectious diseases · 2025Article
- Understanding tinnitus symptom dynamics and clinical improvement through intensive longitudinal data.NPJ digital medicine · 2025Article
- Identification of the microglia-associated signature in experimental autoimmune encephalomyelitis.Frontiers in immunology · 2025Article
- Automated Extraction of Stroke Severity From Unstructured Electronic Health Records Using Natural Language Processing.Journal of the American Heart Association · 2024Article
- Visual detection of seizures in mice using supervised machine learning.bioRxiv : the preprint server for biology · 2024Article
- SCIPAC: quantitative estimation of cell-phenotype associations.Genome biology · 2024Article
- Scoring system for diagnosis and pretreatment risk assessment of neuroblastoma using urinary biomarker combinations.Cancer science · 2024Article
- Factors Affecting Adherence to National Colorectal Cancer Screening: A 12-Year Longitudinal Study Using Multi-Institutional Pooled Data in Korea.Journal of Korean medical science · 2024Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Regularization techniques such as the lasso (Tibshirani 1996) and elastic net (Zou and Hastie 2005) can be used to improve regression model coefficient estimation and prediction accuracy, as well as to perform variable selection. Ordinal regression models are widely used in applications where the use of regularization could be beneficial; however, these models are not included in many popular software packages for regularized regression. We propose a coordinate descent algorithm to fit a broad class of ordinal regression models with an elastic net penalty. Furthermore, we demonstrate that each model in this class generalizes to a more flexible form, that can be used to model either ordered or unordered categorical response data. We call this the
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.