Results 111 to 120 of about 2,640,523 (250)

Ordinal logistic regression for COVID-19 risk (N = 3,106).

, 2022
Ordinal logistic regression for COVID-19 risk (N = 3,106).
Tse-Chuan Yang (798891), Vivian Yi-Ju Chen (12359568), Feinuo Sun (12359571), Kiwoong Park (8022338)   +3 more
core   +1 more source

A Rare De Novo Missense Mutation in IFT122 Confers a Genetic Susceptibility Factor of Idiopathic Pediatric Uveitis Via Trio‐based Whole‐Exome Sequencing

Advanced Science, EarlyView.
A rare de novo IFT122‐A773E variant is identified in idiopathic pediatric uveitis and shown to exacerbate retinal inflammation and barrier dysfunction. Mechanistically, the variant enhances IFT43 interaction, elevates calcium signaling, and activates the MEK/ERK/FRA1 axis, revealing a previously unrecognized cilia‐associated pathway that may increase ...
Qian Zhou, Jiaxing Huang, Yilin Wang, Xingran Li, Xianyang Liu, Lingyu Dai, Hongshun Li, Qingfeng Wang, Jiangyi Liu, Guannan Su, Wanyun Zhang, Yang Deng, Qingfeng Cao, Yujie Lai, Xiang Luo, Changwei Huang, Ling Chen, Shengping Hou, Peizeng Yang   +18 more
wiley   +1 more source

ordinalgmifs: An R Package for Ordinal Regression in High-dimensional Data Settings

Cancer Informatics, 2014
High-throughput genomic assays are performed using tissue samples with the goal of classifying the samples as normal < pre-malignant < malignant or by stage of cancer using a small set of molecular features.
Kellie J. Archer, Jiayi Hou, Qing Zhou, Kyle Ferber, John G. Layne, Amanda E. Gentry   +5 more
doaj   +2 more sources

OSNR Monitoring Using Support Vector Ordinal Regression for Digital Coherent Receivers

IEEE Photonics Journal, 2019
An OSNR monitoring method assisted by support vector ordinal regression (SVOR) is proposed for digital coherent receivers. According to Godard's error of equalized signals obtained after polarization demultiplexing, the optical signal-to-noise ...
Ming Hao, Lianshan Yan, Anlin Yi, Lin Jiang, Yan Pan, Wei Pan, Bin Luo   +6 more
doaj   +1 more source

Ordinal regression analysis of eurobarometer knowledge variable.

, 2018
Ordinal regression analysis of eurobarometer knowledge variable.
Alistair Anderson (5892266)
core   +1 more source

Proteogenomic Profiling of Idiopathic Pulmonary Arterial Hypertension Identifies Sex‐Differential Proteins and Candidate Therapeutic Targets

Advanced Science, EarlyView.
An integrated proteogenomic analysis of 44,137 predominantly European‐ancestry UK Biobank participants aged 40–69 years identifies 12 robust proteins associated with idiopathic pulmonary arterial hypertension. These proteins define a high‐mortality molecular endotype, support early detection and mortality prediction, reveal sex‐differential proteomic ...
Xinjie Lin, Yangchang Zhang, Yang Pu, Duanke Liu, Tao Lei, Kai Ma, Qiyu He, Zheng Dou, Yuze Liu, Dengyuan Liu, Yinge He, Yanshang Wang, Xiaojiao Zheng, Yanbing Ma, Jianrong Zhou, Weiding Zhai, Binbin Su, Li Chen, Shoujun Li   +18 more
wiley   +1 more source

Ordinal Regression Models in Psychology: A Tutorial

, 2019
This Repository contains all source code and data related to the paper "Ordinal Regression Models in Psychology: A ...
Matti Vuorre, Paul-Christian Bürkner
core   +2 more sources

Regression Models for Ordinal Data

Journal of the Royal Statistical Society Series B: Statistical Methodology, 1980
Summary A general class of regression models for ordinal data is developed and discussed. These models utilize the ordinal nature of the data by describing various modes of stochastic ordering and this eliminates the need for assigning scores or otherwise assuming cardinality instead of ordinality.
openaire   +2 more sources

Predicted means from ordinal regression (DM)

, 2018
Predicted means from ordinal regression model for current density by juvenile density treatment ...
Megan L. Vahsen (5026712), J. Grey Monroe (3286101), Ellyn V. Bitume (6001271), Stacy B. Endriss (4340656), Kathryn G. Turner (3274431), Andrew P. Norton (3309249), Ruth A. Hufbauer (616306)   +6 more
core   +1 more source

Towards a Compositional Framework for Describing Human Phenotypes

Advanced Science, EarlyView.
The Phenotype Assembly Method (PhenoAM) decomposes phenotype variables into measurable Features and typed Qualifiers, enabling standardized, machine‐readable Phenome Data Elements (PhenoDEs) that preserve measurement context. Applied in the International Human Phenome Project (IHPP), the framework yields 58 371 PhenoDEs and supports component‐level ...
Wanting Hu, Yunchao Ling, Xinyue Hu, Wei Chen, Rong Zhou, Xinhao Zhuang, Yanfeng Jiang, Jialu Zhao, Xingdong Chen, Jingchun Luo, Li Jin, Guoqing Zhang   +11 more
wiley   +1 more source