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Endogeneity in Logistic Regression Models
To the Editor: Ethelberg et al. (1) report on a study of the determinants of hemolytic uremic syndrome resulting from Shiga toxin–producing Escherichia coli. The dataset is relatively small, and the authors use stepwise logistic regression models to detect small differences.
George Avery +2 more
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Analysis of logistic growth models [PDF]
A variety of growth curves have been developed to model both unpredated, intraspecific population dynamics and more general biological growth. Most predictive models are shown to be based on variations of the classical Verhulst logistic growth equation. We review and compare several such models and analyse properties of interest for these.
A Tsoularis
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Quantitative Models of Fungi Interaction--based on Logistic models [PDF]
As the key medium for decomposing wood fibers, fungi play a vital role in promoting the carbon cycle. The purpose of this paper is to establish mathematic models describing the process of fungi decomposing litter and wood fiber. The paper comprehensively
Zhang Yunfei
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Variable Selection for Spatial Logistic Autoregressive Models
When the spatial response variables are discrete, the spatial logistic autoregressive model adds an additional network structure to the ordinary logistic regression model to improve the classification accuracy. With the emergence of high-dimensional data
Jiaxuan Liang +4 more
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Niels Landwehr +2 more
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Group Logistic Regression Models with lp,q Regularization
In this paper, we proposed a logistic regression model with lp,q regularization that could give a group sparse solution. The model could be applied to variable-selection problems with sparse group structures. In the context of big data, the solutions for
Yanfang Zhang, Chuanhua Wei, Xiaolin Liu
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On the Complexity of Logistic Regression Models [PDF]
We investigate the complexity of logistic regression models, which is defined by counting the number of indistinguishable distributions that the model can represent (Balasubramanian, 1997 ). We find that the complexity of logistic models with binary inputs depends not only on the number of parameters but also on the distribution of inputs in a ...
Nicola Bulso +2 more
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Machine Learning-based Classifiers for the Prediction of Low Birth Weight [PDF]
Objectives Low birth weight (LBW) is a global concern associated with fetal and neonatal mortality as well as adverse consequences such as intellectual disability, impaired cognitive development, and chronic diseases in adulthood.
Mahya Arayeshgari +4 more
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Objective To explore and analyze the influencing factors of multi⁃disciplinary team (MDT) model in treatment of severe traumatic brain injury (sTBI) with severe multiple injuries, and to summarize the diagnosis and treatment experience. Methods Total 144
YANG Zhen⁃yu, XU Xue⁃you
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Study on related risk factors of pain in de novo Parkinson's disease patients
Objective To explore the risk factors of pain in de novo Parkinson's disease (PD) patients. Methods A total of 129 de novo PD patients collected from The Affiliated Brain Hospital of Nanjing Medical University from October 2018 to September 2021 were ...
GUO Zhi⁃ying +5 more
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