APPLICATION OF COX PROPORTIONAL HAZARD REGRESSION FOR ANALYZING FACTORS INFLUENCING THE RECOVERY RATE OF PULMONARY TUBERCULOSIS PATIENTS by Asrul Irfanullah, Ferina Lestari Damamain, Nur Amaliya Tuanaya

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Analyzing individual factors influence on investment processes in regions by N. S. Kagramanyan, S. V. Lukiantseva

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Beyond the Preston Curve: Analyzing Variations in Life Expectancy Around the World Using Multivariate Regression Circa 2000 and 2015 by Jack Homer

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ANALYZING FACTORS OF DIVIDEND POLICY ILLUSTRATED BY COMPANIES OF NASDAQ 100 INDEX by Eugene O. Savchenko, Anna A. Moskaleva

“…From the point of view of getting profits dividend policy is an important factor for investors. It is analyzed regularly, however it is  mainly fragmented and does not show changed taking place. …”
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Factors Affecting Home Injuries in Older Adults: An Analysis Using Binary Logistic Regression by Mehdi Abbasian, Homayoun Sadeghi‐bazargani, Hossein Matlabi, Naser Havaei, Mina Hashemiparast, Hamid Allahverdipour

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Factors influencing sialorrhea in orally intubated patients: a lasso and logistic regression analysis by Jinlei Du, Min Wang, Xiaoling Wu, Tianbo Yu, Jiquan Zhang, Jimin Wu

“…Multivariate logistic regression analysis identified the following as independent risk factors for sialorrhea: Body Mass Index (BMI) (OR = 1.365, 95% CI: 1.217–1.531), Smoking (OR = 8.944, 95% CI: 4.272–18.727), Number of Combined Functional Impairment Systems (OR = 2.844, 95% CI: 1.814–4.460), Combined Oral Disease (OR = 2.578, 95% CI: 1.240–5.359), and Neurological Diseases (OR = 4.040, 95% CI: 1.053–15.507). …”
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A Study of Winning Percentage in the MLB Using Fuzzy Markov Regression by Seung Hoe Choi, Seo-Kyung Ji

“…First, 69 variables for each team are classified into pitching, batting, and fielding using factor analysis, and then the effect of the newly classified variables on the winning percentage is analyzed. …”
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Analysis of influencing factors and trend prediction based on quantile regression and GM(1, 1) model by Lianhui Li, Adham Manyara, Jie Liu

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Multivariate analysis of factors associated with adverse outcomes in UDT children based on retrograde logistic regression model by Kaveh Fathi Vajargah, Enayatollah Homayi Rad, Amir Pirooz

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Investigation of asthenopia prevalence and related factors in university students with ordered logistic regression by Halil Sengul

“…Results: Results showed that 75.6% of participants experienced asthenopia; the most common symptom was eyestrain (37.6%). Logistic regression analysis revealed that women were 3.385 times more likely to develop asthenopia than men. …”
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Key Influencing Factors of Urban Flooding in Wuhan Based on Multi-scale Geographically Weighted Regression Model by HUANG Zi-ye, YANG Qing-yuan, WEI Hong-yan

“…Many studies have used the Geographically Weighted Regression (GWR) model to analyze the causes of urban flooding, but its limitation lies in ignoring the scale variations in spatial heterogeneity in various influencing factors. …”
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Analysis of Factors Influencing Repurchase Decision of Flight Tickets of Garuda Indonesia Airlines Using Binary Logistic Regression by Rizki Agung Ramadani, Tiyanda Hanti Arum Kusuma, Rinta Agustiani Dwiputri, Jerry Heikal

“… The aviation industry in Indonesia is one of the sectors that has experienced rapid growth along with the increasing mobility of society and the need for air transportation. This study aims to analyze the factors that influence the decision to repurchase airline tickets at Garuda Indonesia Airlines using the Binary Logistic Regression method. …”
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The Agricultural Factors Influencing the Economic Development of Kazakhstan by A. K. Jussibaliyeva, A. B. Soltanbayeva, S. S. Tleuberdiyeva

“…Using the SPSS program, a multiple regression analysis was performed to investigate the relationship between six independent variables and one dependent variable of economic growth expressed as GDP per capita. …”
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SPATIAL MODELING OF MATERNAL HEALTH: GEOGRAPHICALLY WEIGHTED POISSON REGRESSION ON MATERNAL MORTALITY FACTORS by Alfa Yuliana, Achmad Fauzan

“…This study aims to evaluate the effectiveness of Poisson regression, negative binomial regression, and Geographically Weighted Poisson Regression (GWPR) models in capturing the variability of maternal deaths in the study area for that year. …”
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The study on risk assessment of carotid plaques in the Northern Chinese population based on LASSO regression by Kun Yuan, Chongjian Li, Junmin Chu, Yilin Huang, Jiayi Song, Liguang Dong, Ying Yang, Hongyu Wang, Jinbo Liu, Xinhua An, Xiaoyuan Tian, Lin Mu, Ye Tian, Zengwu Wang, Linfeng Zhang

“…Carotid plaques were assessed via carotid ultrasound. LASSO regression was used for feature selection, logistic regression was employed to analyze risk factors, and a risk assessment nomogram was also developed.. …”
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Classification and Regression Tree Analysis in Adult Hemophagocytic Syndrome: Identifying Acute Heart Failure Predictors in ICU Patients by Kilincer Bozgul SM, Kurtulmus IA, Yargucu Zihni F, Akad Soyer N, Yagmur B, Gunes A, Koymen G, Bozkurt D

“…This study aimed to identify predictors of acute heart failure in HPS patients using classification and regression tree (CART) analysis.Methods: A retrospective analysis was performed on 146 HPS patients without a diagnosis of HF. …”
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AN ORDINAL LOGISTIC REGRESSION MODEL FOR ANALYZING RISK ZONE STATUS OF COVID-19 SPREAD by Tessya Mutiara Dewi, Rosita Kusumawati

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Analysis of risk factors and intervention measures for postoperative bleeding in patients with diabetes after proctologic surgery based on a logistic regression model by Qiuxiang Yu, Peiyao Li, Dan Li, Lin Wang, Guoshuang Yu, Rui Li

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An analysis of the factors influencing engagement metrics within the dissemination of health science misinformation by Ruofei Chen, Guoyong Chen, Li Zhang, Ruiqian Xie, Ruopeng Chen

“…A combined weighting method, using the entropy weight method and the analytic hierarchy process (AHP), was employed, followed by sensitivity analysis to determine activity levels. Non-parametric tests and negative binomial regression models were used to analyze the key influencing factors of misinformation activity.ResultsWeChat exhibited the highest proportion of health misinformation (44.95%), with the majority originating from individual authors (55.96%), and primarily positive sentiment (37.61%). …”
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Analysis of the significance and gender differences in the factors influencing antisocial behaviors among adolescents by Wenze Sui, Yan Gao, Liangyu Zhao, Yuke Yang, Lu Chen, Yining Hu, Xiangren Yi, Shuoqin Zhang, Sen Ma

“…Random forest was used to assess the importance of influencing factors, and binary logistic regression analysis was conducted on the top eight identified factors. …”
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