A Safe Location for a Trip? How the Characteristics of an Area Affect Road Accidents—A Case Study from Poznań by Cyprian Chwiałkowski

“…For the purposes of the analysis, two variants of the regression method were used: ordinary least squares (OLS) and geographically weighted regression (GWR). …”
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The factors that influence audit quality by earnings surprise benchmark by Vina Aqmarina, Reni Yendrawati

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Trends of road traffic mortality in Tehran city during 2012-2021 by Amir Kavousi, Khaled Rahmani, Ali Moradi, Fatemeh Darabi, Mohammad Razeghi

“…Geographic and land feature data were collected from the Mapping Organization and the Statistical Center of Iran. Spatial data were analyzed using specialized statistical methods. To examine the impact of local and regional factors on road traffic deaths and to assess trends over the study period, generalized Poisson regression and negative binomial regression models were utilized.Results: Among Tehran's urban regions, Region 15 reported the highest number of fatal accidents, with 711 cases, while Region 13 had the lowest frequency, recording 113 cases. …”
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DEVELOPING A PREDICTIVE MODEL OF SOCIAL COGNITIVE INFLUENCES ON PHYSICAL ACTIVITY IN MIDDLE-AGED AND OLDER ADULTS: A CROSS-SECTIONAL STUDY by Novita Intan Arovah, Juni Kurniawaty, Hartiah Haroen

“…A 7-day Physical Activity Recall interview was conducted to measure MVPA. Data were analyzed using bivariate correlations and stepwise multiple linear regressions, adjusted for sex and age. …”
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Protein losses caused by peritoneal dialysis and influencing factors by TANG Xing-ming, HU Jie-ping, DENG Hui-zhao, LIN Jian, ZHENG Wei-ping, ZOU Zhao-hui

“…The amount and component of the protein in dialysate were accessed by the immunoturbidimetry and electrophoresis,and the demographic data and clinical data were collected to analyze the difference between the two groups. The logistic regression was applied to disclose the risk factors of the protein losses via dialysate. …”
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China’s Spatial Economic Network and Its Influencing Factors by Guihai Yu, Deyan He, Wenlong Lin, Qiuhua Wu, Jianxiong Xiao, Xiaofang Lei, Zhongqun Xie, Renjie Wu

“…Finally, we employ Quadratic Assignment Procedure (QAP) regression analysis to analyze the influential factors on spatial economic network. …”
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Income Inequality Shift Paradigm. From Economic Approach to Sharing Responsibilities by Claudia-Andreea Toma, Cristina Boboc, Valentina Vasile, Simona Ioana Ghiță

“…The use of the panel data regression model allows country specific effects control, the results showing that in the context of European convergence, the historical, political, cultural and socio-demographic factors have the greatest impact in terms of income distribution. …”
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Risk Factors and Predictive Models for Sarcopenia in Older Adults by Shiyuan Zhang, Xue Yang, Nina An, Meng Lv, Lanyu Yang, Rui Liu, Song Hu, Weiguo Chen, Wenjing Feng, Yongjun Mao

“…LASSO and logistic regression models were constructed to identify and evaluate significant risk factors for sarcopenia. …”
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Association between blood lead levels and constipation in adults: insights from NHANES data (2005–2010) by Yue-Juan Li, Hui Dong, Wen-Xing Chen, Deng-Chao Wang, Miao Yu

“…Abstract Background Constipation is a common health issue affecting quality of life. While environmental factors like lead exposure may influence gastrointestinal function, the link between blood lead levels and constipation is underexplored. …”
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Length–weight relationships, condition factor and relative condition factor of blood cockle, Tegillarca granosa (L. 1758) collected from the west coast of Cox’s Bazar, Bangladesh... by Tanjuma Tasnim Hira, Fauzia Mashkura Nishat, Mahfuza Anika, Sanjida Afrin Semme, Md. Jasim Uddin

“…A total of 240 individuals shell length (SL) ranging from 3.6 to 6.9 cm, shell height (SH) varying from 3.5 to 5.8 cm, shell thickness (ST) changing from 3.3 to 5.1 cm and tissue wet weight (TWW) deviating from 5.5 to 20.9 g were analyzed. The regression equation established for SL-TWW, SH-TWW and ST-TWW were SL = 0.16 × SL2.476 (r2 = 0.815), TWW = 0.45 × SH2.262 (r2 = 0.681) and ST = 0.43 × ST2.203 (r2 = 538) respectively. …”
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Harnessing Socio-Spatial Dynamics for Pandemic Resilience: Evidence from Kozhikode, India by Shahana Usman Abdulla, Bimal Puthuvayi

“…Based on the data collected from 1194 individuals across 75 wards of Kozhikode City, the study employed a binary logistic regression model to examine how these variables affect COVID-19 test outcomes and a hotspot analysis to analyze the spatial dynamics of infection. …”
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The more the better? The effect of person-job fit on work engagement by Juliana Barreiros Porto, Lígia Carolina Oliveira-Silva, Elis Calcagno Martins

“…A sample of 341 workers responded to the Engagement at Work and Work Design scales. Confirmatory factor analysis, polynomial regression, and response surface analysis were used to test the hypotheses. …”
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ANALISIS FAKTOR YANG MEMPENGARUHI STATUS PENERIMAAN BERAS KELUARGA MISKIN MENGGUNAKAN REGRESI LOGISTIK BINER DI KECAMATAN LANGSA BARAT by Amelia Amelia, Fitra Mulyani, Ulya Nabilla

“…Therefore this study aims to analyze the significant factors that affect the status of rice in poor families using binary logistic regression analysis. …”
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Determinants Of Stock Price Factors In The Jakarta Islamic Index by Adriana Kuswara, Damayanti Damayanti

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Changes in the Suicide Rate under the Influence of Daily Activities in EU Countries by P. A. Korotkov, A. B. Trubyanov, E. A. Zagaynova, A. I. Zverev

“…Daily activities are understood as time spent on work, household and leisure activities. In order to analyze the relation between the variables an end-to-end linear regression model arranged by all years and countries is used; the panel data structures are not taken into account in the model (as we have to deal with pseudo panel data). …”
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Predictors of exclusive breastfeeding: a systematic review and meta-analysis by Mehri Kalhor, Mansoureh Yazdkhasti, Masoumeh Simbar, Sepideh Hajian, Zahra kiani, Behjat Khorsandi, Mahtab Sattari, Zainab Ezadi, Haniyeh Nazem, Massoma Jafari

“…This study systematically reviews and analyzes the predictors of EBF. Methods This study is a systematic review and meta-analysis. we searched electronic databases including PubMed/MEDLINE, Web of Science, PsycINFO, Cochrane, Scopus, EMBASE, Google Scholar, SID, and Magiran. we examined articles published between 2000 to 2023 using keywords like "risk factors", "related factors", "predictive factors", "exclusive breastfeeding ", and "women". …”
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Fertility intentions among Chinese adults: a cross-sectional study using a national survey by Mingyan Hao, Chenxiao Zhang, Haofeng Fu, Jingting Zhang, Ziyi Zhang, Baotong Ma, Ruitong Xia, Yuanwei Lu, Jingwen Liu, Hanjia Xin, Yumeng Cao, Saier Yang, Runqing Li, Ji Zhao, Jin Zhang, Zheng Gao, Yaxin Zeng, Yixiao Ding, Zhuolun Ren, Yan Guan, Na Zhang, Jia Li, Yan Ma, Pei Wei, Jingjing Dong, Chen Chen, Yajing Zhou, Jianzhong Zheng, Wei Liu, Lizheng Wang

“…This situation necessitates a thorough examination of the multiple underlying factors that contribute to individuals’ decisions regarding family size. …”
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Prediction of the incidence of lyme disease using mathematical modeling methods (using the example of the Kirov region) by Elena O. Utenkova, Ilya S. Knyazhev, Nikolay S. Shchur

“…The aim of the study is to analyze the influence of various factors on the incidence of Lyme disease using mathematical modeling methods for further epidemiological forecasting using the example of the Kirov region. …”
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Macroeconomic Determinants of Total Factor Productivity: An Analysis on the Example of OECD Countries by Nadide Yiğiteli, Fahriye Öztürk

“…Subsequently, the effect of these variables on TFP is investigated using panel regression methods. Results reveal that the technology diffusion index, which depicts the mechanisms of technology transfer from country to country, is the most important factor determining TFP. …”
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Risk factor and operation influence of intracranial hemorrhage following ventriculoperitoneal shunt by Wei Wang, Jun Lin, Xiaoming Guo, Shiqi Gao, Junming Zhu, Yuan Hong

“…This study aimed to identify and assess the risk factors associated with intracranial hemorrhage in patients undergoing VP shunt surgery. …”
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