Results 61 to 70 of about 2,451,188 (298)

Determining the factors affecting the happiness levels of divorced individuals by ordered logistics regression analysis

MANAS: Journal of Engineering, 2022
In cases where the dependent variable is categorical and ordinal, the Ordinal Logistic Regression Model is used for model estimation. In order to predict the Ordinal Logistic Regression Model, it must provide the parallel lines assumption.
Burak Uyar, Cevdet Büyüksu
doaj   +1 more source

Data‐Driven SuStaIn Model of Disability Progression in Amyotrophic Lateral Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To determine whether ordinal Subtype and Stage Inference (SuStaIn) applied to routine ALSFRS‐R item scores can identify reproducible disability progression patterns in amyotrophic lateral sclerosis (ALS) and provide clinically meaningful staging.
Giammarco Milella, Veria Vacchiano, Vittorio Velucci, Stefano Zoccolella, Rocco Liguori, Giovanni Defazio   +5 more
wiley   +1 more source

Exploiting Structured Global and Neighbor Orders for Enhanced Ordinal Regression

Information
Ordinal regression combines classification and regression techniques, constrained by the intrinsic order among categories. It has wide-ranging applications in real-world scenarios, such as product quality grading, medical diagnoses, and facial age ...
Imam Mustafa Kamal, Solichin Mochammad, Latifah Nurahmi, Azis Natawijaya, Muhammad Kalili   +4 more
doaj   +1 more source

Ordinal Logistic Regression Analysis in Determining Factors Associated with Socioeconomic Status of Household in Tepi Town, Southwest Ethiopia

The Scientific World Journal, 2022
Background. Socioeconomic status (SES) refers to an individual’s or group’s social position or class, which is often determined by a combination of education, income, and occupation.
Mesfin Esayas Lelisho, Abebe Argaw Wogi, Seid Ali Tareke   +2 more
doaj   +1 more source

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

Early Clinical and Cerebrospinal Fluid Predictors of 1‐Year Recurrence in Autoimmune GFAP Astrocytopathy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Autoimmune glial fibrillary acidic protein astrocytopathy (GFAP‐A) is an inflammatory central nervous system disorder with variable outcomes. Relapse occurs in a subset of patients, but early predictors remain unclear. We aimed to identify admission‐available features associated with 1‐year recurrence and develop an interpretable ...
Qingting Hong, Yuping Xiao, Yuhan Wu, Ziyuan Huang, Weishan Liang, Li Xiao, Yaqing Shu, Tingting Lu, Yanyu Chang, Wei Qiu, Yuge Wang   +10 more
wiley   +1 more source

Factors Influencing Satisfaction with Patient-Controlled Analgesia Among Postoperative Patients Using a Generalized Ordinal Logistic Regression Model

Asian Nursing Research, 2020
Summary: Purpose: The purpose of this study was to identify the factors affecting the satisfaction with patient-controlled analgesia (PCA) of patients using a generalized ordinal logistic regression model and to evaluate the difference in results of the
Wonhee Baek, Yeonsoo Jang, Chang Gi Park, Mir Moon   +3 more
doaj   +1 more source

Systemic Extracerebral Atherosclerotic Burden and Dementia Risk After Incident Stroke

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Stroke survivors are at increased risk of dementia, but clinically accessible markers of risk heterogeneity remain limited. Previous studies have largely examined atherosclerotic disease in individual vascular beds rather than the overall burden of systemic extracerebral atherosclerosis.
Zhexuan Yu, Tianxue Chen, Wei Jin, Weifeng Jin, Haitong Wan   +4 more
wiley   +1 more source

On the Consistency of Ordinal Regression Methods

J. Mach. Learn. Res., 2014
Many of the ordinal regression models that have been proposed in the literature can be seen as methods that minimize a convex surrogate of the zero-one, absolute, or squared loss functions. A key property that allows to study the statistical implications of such approximations is that of Fisher consistency.
Pedregosa, Fabian, Bach, Francis, Gramfort, Alexandre   +2 more
openaire   +4 more sources

Ordinal Regression Analysis: Using Generalized Ordinal Logistic Regression Models to Estimate Educational Data [PDF]

, 2012
The proportional odds (PO) assumption for ordinal regression analysis is often violated because it is strongly affected by sample size and the number of covariate patterns.
Liu, Xing, Koirala, Hari, Xing Liu, Hari Koirala   +3 more
core   +1 more source