Results 91 to 100 of about 840,245 (337)

Retrospective-prospective symmetry in the likelihood and Bayesian analysis of case-control studies

, 2013
Prentice & Pyke (1979) established that the maximum likelihood estimate of an odds-ratio in a case-control study is the same as would be found by running a logistic regression: in other words, for this specific target the incorrect prospective model is ...
Byrne, Simon P. J., Dawid, A. Philip
core   +1 more source

Multinomial and ordinal Logistic regression analyses with multi-categorical variables using R

Annals of Translational Medicine, 2020
Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai 200032, China Correspondence to: Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai 200032, China.
Jiaqi Liang, Guoshu Bi, C. Zhan
semanticscholar   +1 more source

Macrophage Phenotype Detection Methodology on Textured Surfaces via Nuclear Morphology Using Machine Learning

Advanced Intelligent Discovery, EarlyView.
A novel machine learning approach classifies macrophage phenotypes with up to 98% accuracy using only nuclear morphology from DAPI‐stained images. Bypassing traditional surface markers, the method proves robust even on complex textured biomaterial surfaces. It offers a simpler, faster alternative for studying macrophage behavior in various experimental
Oleh Mezhenskyi, Kateryna Andriienkova, Tetyana Goldanova, Ezgi Antmen, Thibaut Soubrie, Nihal Engin Vrana   +5 more
wiley   +1 more source

A study of correlations between metabolic syndrome factors and osteosarcopenic adiposity

BMC Endocrine Disorders, 2021
Background Aging reduces the quality and strength of bones and muscles and increases body fat, which can lead to the simultaneous occurrence of sarcopenia, osteopenia, and adiposity, a condition referred to as OsteoSarcopenic Adiposity (OSA).
Yu-Hsiang Su, Yu-Ming Chang, Chih-Ying Kung, Chiu-Kuei Sung, Wei-Shin Foo, Mei-Hua Wu, Shang-Jyh Chiou   +6 more
doaj   +1 more source

Estimasi Parameter Regresi Logistik Multinomial Dengan Metode Bayes [PDF]

, 2013
Multinomial logistic regression is a logistic regression where the dependent variable is polychotomous is dependent variable value of more than two categories.
Apsari, W. (Wayaning), Sugito, S. (Sugito), Yasin, H. (Hasbi)   +2 more
core  

IAR‐Net: Tabular Deep Learning Model for Interventionalist's Action Recognition

Advanced Intelligent Systems, EarlyView.
This study presents IAR‐Net, a deep‐learning framework for catheterization action recognition. To ensure optimality, this study quantifies interoperator similarities and differences using statistical tests, evaluates the distribution fidelity of synthetic data produced by six generative models, and benchmarks multiple deep‐learning models.
Toluwanimi Akinyemi, Olatunji Omisore, Wenjing Du, Wenke Duan, Chen Bailang, Liu Kun, Lei Wang, Minxin Wei   +7 more
wiley   +1 more source

Settlement Intention of Foreign Workers in Japan: Bayesian Multinomial Logistic Regression Analysis

Economies
This study examines the intentions of foreign workers living in Okayama, Japan, to stay long-term in Japan. Utilizing a Bayesian multinomial logistic regression model, this research provides a novel analytical approach that captures parameter uncertainty
Mi Moe Thuzar, Shyam Kumar Karki, Andi Holik Ramdani, Waode Hanifah Istiqomah, Tokiko Inoue, Chukiat Chaiboonsri   +5 more
doaj   +1 more source

Epidemiological pattern of trauma patients based on the mechanisms of trauma: trends of a regional trauma center in Midwest of Iran

BMC Emergency Medicine, 2022
Introduction Trauma is one of the important issues in public health because it is responsible for 90% of mortality in Low and Middle-Income Countries (LIMCs).
Ghodratollah Roshanaei, Sahar Khoshravesh, Sajjad Abdolmaleki, Tayebeh Bathaei, Mahnaz Farzian, Mohammadreza Saatian   +5 more
doaj   +1 more source

Categorical data analysis using a skewed Weibull regression model

, 2017
In this paper, we present a Weibull link (skewed) model for categorical response data arising from binomial as well as multinomial model. We show that, for such types of categorical data, the most commonly used models (logit, probit and complementary log-
Caron, Renault, Dey, Dipak, Polpo, Adriano, Sinha, Debajyoti   +3 more
core   +2 more sources

Factors influencing unmet need for family planning among Ghanaian married/union women: a multinomial mixed effects logistic regression modelling approach

Archives of Public Health, 2019
BackgroundUnmet need for family planning is high (30%) in Ghana. Reducing unmet need for family planning will reduce the high levels of unintended pregnancies, unsafe abortions, maternal and neonatal morbidity and mortality. The purpose of this study was
C. Guure, E. Maya, Samuel K. K. Dery, Baaba da-Costa Vrom, R. Alotaibi, H. Rezk, A. Yawson   +6 more
semanticscholar   +1 more source