Are Risk Attitudes and Individualism Predictors of Entrepreneurship? A Multivariate Analysis of Romanian Data by Adrian Hatos, Roxana Hatos, Alina Bădulescu, Daniel Bădulescu

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Multivariate logistic regression analysis to explore the high-risk factors of deep vein embolism/pulmonary embolism after knee replacement in the elderly by Ming Liu, Zhanwen Zhou, Xiaohu Ma, Jinguo Ma, Xiaojin Wu, Binghan Chen, Yanbin Tian

“…The incidence of DVT/PE was significantly higher in the very high-risk group compared to the high-risk group (9.89% vs 4.84%, χ 2 = 2.080, p = .032). Multivariate logistic regression analysis identified the Caprini score as an extremely high-risk factor (adjusted OR = 2.87, 95% CI: 1.53-5.39, p = .001), alongside COPD (OR = 1.94, 95% CI: 1.08-3.48, p = .026), history of heart failure (OR = 1.68, 95% CI: 1.01-2.78, p = .048), and surgical duration exceeding 2 hours (OR = 1.35, 95% CI: 1.08-1.68, p = .008) as independent risk factors. …”
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Investigating the Effect of Profit Predictability Criteria and the Relevance of Financial Information on the Readability of Companies' Annual Reports, Using Fogg's Index and Multiv... by Mostafa Matinnazar, Naghi Fazeli, Arezoo Khosravani, Amir Yalfani

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Risk prediction and clinical utility analysis of postoperative pancreatic fistula: a comparative study of multivariable logistic regression and random forest models by Kaixuan Zhang, Kunlun Chen

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Do All Children with Epilepsy have Behavioural Problems? A Multivariate Risk Factor Analysis by Shashank Nayak, Puneet Mathur, Ashok Kumar Jain, Himanshu Agrawal, Rahul Bhargava, Amit Gupta, Niti Tripathi

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Development of a Metabolic Syndrome Prediction Model Using HOMA-IR and Multivariate Factors by An-Sik Heo, Jung-Chul Lee

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Coexisting predictors for undernutrition indices among under-five children in West Africa: application of a multilevel multivariate ordinal logistic regression model by Abebew Aklog Asmare, Awoke Seyoum Tegegne, Denekew Bitew Belay, Yitateku Adugna Agmas

“…Considering the impact of other predictors such as maternal, child, and socioeconomic variables, a multilevel multivariate partial proportional ordinal logistic regression model was conducted to analyze the relationship between stunting, wasting and underweight. …”
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Academic burnout syndrome associated with anxiety, stress, depression, and quality of life in Peruvian dentistry students: an analysis using a multivariable regression model by José Menacho-Rivera, Leonor Castro-Ramirez, Enrique Yarasca-Berrocal, José Huamani-Echaccaya, Cinthia Hernández-Vergara, Marysela Ladera-Castañeda, César Cayo-Rojas

“…The confounding variables considered included age, sex, year of study, marital status, and place of origin. A Poisson regression model with robust variance was used for multivariable analysis, employing adjusted prevalence ratios (APR). …”
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Enhancing intracranial aneurysm rupture risk prediction with a novel multivariable logistic regression model incorporating high-resolution vessel wall imaging by Zihang Wang, Zihang Wang, Chang Yan, Chang Yan, Wenqing Yuan, Wenqing Yuan, Shuangyan Jiang, Shuangyan Jiang, Yongxiang Jiang, Ting Chen

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Тotal probability formula for vector Gaussian distributions by V. S. Mukha, N. F. Kako

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Comprehensive Analysis of Soil Physicochemical Properties and Optimization Strategies for “<i>Yantai Fuji 3</i>” Apple Orchards by Zhantian Zhang, Zhihan Zhang, Zhaobo Fan, Weifeng Leng, Tianjing Yang, Jie Yao, Haining Chen, Baoyou Liu

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Using multivariate analyses to evaluate the impact of proline on sugar and root yield traits in sugar beet under saline conditions by Farrag F. B. Abu-Ellail, Noran A. M. Bassiony, Ramy N. F. Abdelkawy

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Quantitative Evaluation of Rotational Wood Welding Joint Strength Based on Regression of Data Sets by Yun Xu, Xuejiao Wang, Aleksandr G. Chernykh, Roshchina I. Svetlana, Pavel S. Koval, Egor V. Danilov, Anatoly Y. Naichuk

“…For instance, (1) A comprehensive database of 689 previously published trials was curated to identify key factors: substrate diameter, effective welded length, and substrate density. (2) Comparative analysis of test outcomes and predictive models revealed consistent trends, suggesting that modeling techniques for self-tapping wood screws could be applied to rotational wood welding joints. (3) Univariate linear regression validated the primary factors, leading to a multivariate model for predicting withdrawal capacity. …”
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Generalized linear models applied to the analysis of the effectiveness of the Sterile Insect Technique by Guilherme Rodrigues, Ariane Campolim Cristino, Daniela R. Cantane, Helenice O. Florentino, Marco A. R. Fernandes, Paulo E. M. Ribolla, Rogerio A. Oliveira

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Prediction of permeability and porosity from well log data using the nonparametric regression with multivariate analysis and neural network, Hassi R’Mel Field, Algeria by Baouche Rafik, Baddari Kamel

“…We propose a two-step approach to permeability prediction that utilizes non-parametric regression in conjunction with multivariate statistical analysis. …”
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Identifying Individual and Household Level Predictors of Undernutrition Among 6–59 Months Children in Bangladesh: A Multivariate Approach by Oumma Halima, Abira Nowar, Md. Hafizul Islam, Akibul Islam Chowdhury, Kazi Turjaun Akhter, Nazma Shaheen

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APPLICATION AND PERFORMANCE COMPARISON OF MULTI-OUTPUT MACHINE LEARNING FOR NUMERICAL-NUMERICAL AND NUMERICAL-CATEGORICAL OUTPUTS by Karin Joan, Robyn Irawan, Benny Yong

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Maximum Dry Unit Weight and Optimum Moisture Content Prediction of Lateritic Soils Using Regression Analysis by Yufeng Qian

“…The purpose is to evaluate the applicability of multivariate adaptive regression splines (MARS) for estimating γdmax and ωopt of lateritic soils. …”
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Forecasting water quality indices using generalized ridge model, regularized weighted kernel ridge model, and optimized multivariate variational mode decomposition by Marjan Kordani, Mohsen Bagheritabar, Iman Ahmadianfar, Arvin Samadi-Koucheksaraee

“…Statistical metrics confirmed that the proposed OMVMD-GRKR model, concerning the best efficiency in the Ahvaz (R = 0.987, RMSE = 0.761, and U95% = 2.108) and Molasani (R = 0.963, RMSE = 1.379, and U95% = 3.828) stations, outperformed the OMVMD and simple-based methods such as ridge regression (Ridge), least squares support vector machine (LSSVM), deep random vector functional link (DRVFL), and deep extreme learning machine (DELM). …”
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DIAGONALISASI MATRIKS UNTUK MENYELESAIKAN MODEL MANGSA-PEMANGSA by Elvinus R. Persulessy

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