Hypothyroidism is Not Associated with Keratoconus Disease: Analysis of 626 Subjects by Zsuzsa Flaskó, Elena Zemova, Timo Eppig, László Módis, Achim Langenbucher, Stefan Wagenpfeil, Berthold Seitz, Nóra Szentmáry

“…A multiple logistic linear regression model was constructed to determine the effects of age (covariate), gender, and hypothyroidism (effect sizes) on “TKC-positive” disease. …”
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Comparison of 1D and 3D volume measurement techniques in NF2-associated vestibular schwannoma monitoring by Isabel Gugel, Nuran Aboutaha, Bianca Pfluegler, Ulrike Ernemann, Martin Ulrich Schuhmann, Marcos Tatagiba, Florian Grimm

“…The Hannover and Koos classification was used to depict the size ratio in each MRI and tumor. A linear regression model was performed to compare 1D/classification systems to SVA, and the percentage deviation change of MLD3 and OA to SVA was established using a one-way multivariate variance analysis. 2586 SVA and 10344 linear measurements were performed in a cohort of 149 NF2 patients and 292 associated VS. …”
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Prevalence of depression, anxiety, and stress among students enrolled at King Khalid University: a cross-sectional study by Abdulaziz M. Al-Garni, Ayed A. Shati, Nora A. Almonawar, Ghadi M. Alamri, Lujain A. Alasmre, Thamraa N. Saad, Faisal M. Alshehri, Esraa Abdellatif Hammouda, Ramy Mohammed Ghazy

“…A multivariate linear regression model was used to examine the relationships between the independent variables (age, gender, academic year, and study field) and the dependent variables (depression, anxiety, and stress). …”
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 Increasing the resolution of malaria early warning systems for use by local health actors by Michelle V. Evans, Felana A. Ihantamalala, Mauricianot Randriamihaja, Vincent Herbreteau, Christophe Révillion, Thibault Catry, Eric Delaitre, Matthew H. Bonds, Benjamin Roche, Ezra Mitsinjoniala, Fiainamirindra A. Ralaivavikoa, Bénédicte Razafinjato, Oméga Raobela, Andres Garchitorena

“…A spatio-temporal hierarchical generalized linear regression model was trained on monthly malaria case data from 195 communities from 2017 to 2020 and evaluated via cross-validation. …”
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Evaluation of Hospitalized Patients with Diabetes Mellitus with the International Classification of Functioning, Disability and Health Rehabilitation Set by LU Weiyan, TANG Dandan, ZHU Junzhi, LIU Yingfen, DU Lishi, WANG Haoxiang

“…With ICF-RS standardization results as dependent variable and factors affecting patients' function in univariate analysis as independent variables, a multiple linear regression model (<italic>F</italic>=22.558, <italic>P</italic>&lt;0.001) was established. …”
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Farm factors associated with increased free fatty acids in bulk tank milk by Hannah M. Woodhouse, Stephen J. LeBlanc, Trevor J. DeVries, Karen J. Hand, David F. Kelton

“…In the final multivariable linear regression model, milking frequency ≥3×/d (times per day) compared with <3×/d was associated with a greater FFA concentration in AMS (β = 0.27, 95% CI: 0.12, 0.41) and tiestall milking systems (β = 1.17, 95% CI: 0.76–1.59). …”
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Hemoglobin glycation index and mortality risk in metabolic dysfunction-associated steatotic liver disease patients: a novel U-shaped association by Mengjie Zhao, Ning Sun, Yurong Cheng, Wantong Zhang, Jinjin Ji, Qiuyan Li, Fang Lu, Weiliang Weng

“…The HGI was determined using a linear regression model that correlated hemoglobin A1c (HbA1c) with fasting plasma glucose (FPG). …”
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Prediction of coal dust particle size after spraying dust reduction in roadway based on orthogonal experiment and regression analysis by Bingyou JIANG, Yuqian ZHANG, Changfei YU, Ben JI, Haoyu WANG, Zhuang LIU

“…On this basis, combined with the weights of each influencing factor, a weighted-based multivariate nonlinear regression prediction model of coal dust D90 after spraying dust reduction was constructed, and its prediction results were compared and analyzed with those of the multivariate linear regression model. The results show that: the coal dust D90 after spray dust reduction decreases with the increase of the distance from the dust source to the spray frame, increases and then decreases with the increase of wind speed, and increases with the increase of water supply pressure, and there is a strong positive correlation between full dust, exhaled dust reduction efficiency and D90, the better the spray dust reduction effect, the larger the coal dust D90 after spray dust reduction; the weighting-based prediction model of coal dust D90 after dust spraying has higher accuracy and smaller error, and can accurately characterize the quantitative relationship between coal dust D90 after dust spraying and three influencing factors, namely, the distance of the spray frame from the dust source, the wind speed of the roadway, and the water supply pressure of the nozzle.…”
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Long-term changes in the thermodynamic structure of the lowermost stratosphere inferred from reanalysis data by F. Weyland, P. Hoor, D. Kunkel, T. Birner, T. Birner, F. Plöger, F. Plöger, K. Turhal, K. Turhal

“…The trend analysis is performed with a dynamic linear regression model (DLM), capable of modeling non-linear trends. …”
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Relationship between dietary intake and growth and development in Chinese pupils by Wen Fang, Ye Fu, Qin Li, Menghan Cheng, Miao Zhang, Yu Lu

“…The multivariate generalized linear regression models adjusted for covariates were used to investigate the association between dietary intake and growth and development of pupils.ResultsThe generalized linear regression model showed that standing long jump of all pupils (β = −6.735, 95% CI: −12.064, −1.406) and body fat rate (β = −2.650, 95% CI: −4.794, −0.507), fat weight (β = −1.283, 95% CI: −2.286, −0.280) and chest circumference (β = −1.456, 95% CI: −2.789, −0.123) of boys were negatively correlated with dietary diversity score. …”
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A cross-sectional study of parental perspectives on children about COVID-19 and classification using machine learning models by Fahmida Kousar, Arshiya Sultana, Marwan Ali Albahar, Manoj Shamkuwar, Md Belal Bin Heyat, Mohd Ammar Bin Hayat, Saba Parveen, John Irish G. Lira, John Irish G. Lira, Khaleequr Rahman, Abdullah Alammari, Eram Sayeed

“…The analysis utilised the Generalised Linear Regression Model (GLM), K-Nearest Neighbours (KNN), Support Vector Machine (SVM), Random Forest (RF), Naive Bayes (NB), and AdaBoost (AB).ResultsThe study revealed an average knowledge score of 18.02 ± 2.9, with 43.2 and 52.9% of parents demonstrating excellent and good knowledge, respectively. …”
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Automated quantification of anterior chamber cells using swept-source anterior segment optical coherence tomography by Shani Pillar, Shin Kadomoto, Keren Chen, Saitiel Sandoval Gonzalez, Nina Cherian, Joseph K. Privratsky, Nicolette Zargari, Nicholas J. Jackson, Giulia Corradetti, Judy L. Chen, SriniVas R. Sadda, Gary N. Holland, Edmund Tsui

“…Automated counts were compared to SUN grades using a mixed-effects linear regression model. Results 90 eyes (54 participants) were included; 67 eyes (41 participants) had histories of uveitis, while 23 eyes (13 healthy participants) served as controls. …”
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Testicular biometrics of Murrah buffaloes in different age groups by Erly L. Carrascal-Triana, Jorge Mejía Lúquez, Divier Agudelo Gómez, Edison Julián Ramírez Toro

“…Descriptive statistics were performed for each variable; for the SC and TV, a linear regression model as a function of age and weight was analyzed, and simple Pearson correlations were performed. …”
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Exploring the potential association between serum selenium and hypertension in obese adult males in the United States by Bei Li, Haiyan Ma, Ying Yu, Jieli Chen, Shengnan He, Lan Yang

“…To examine the saturation threshold effect between serum selenium and hypertension, a generalized additive model (GAM) and a two-piecewise linear regression model were employed. Furthermore, the saturation threshold effect was evaluated separately in subgroups stratified by BMI and age. …”
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A long-term drought reconstruction based on oxygen isotope tree ring data for central and eastern parts of Europe (Romania) by V. Nagavciuc, V. Nagavciuc, G. Helle, M. Rădoane, C.-C. Roibu, M.-G. Cotos, M. Ionita, M. Ionita

“…This highlights SPEI9 as a superior indicator of drought compared to individual parameters like temperature or precipitation. Using a linear regression model, we reconstructed August SPEI9 variability for the past 200 years. …”
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Mental health in the COVID-19 pandemic: A longitudinal analysis of the CLoCk cohort study. by Laura Panagi, Simon R White, Snehal M Pinto Pereira, Manjula D Nugawela, Isobel Heyman, Kishan Sharma, Terence Stephenson, Trudie Chalder, Natalia K Rojas, Emma Dalrymple, Kelsey McOwat, Ruth Simmons, Olivia Swann, CLoCk Consortium, Tamsin Ford, Roz Shafran

“…Findings from multilevel mixed-effects linear regression model showed that on average mental health symptoms as measured by the total SDQ score increased over time (B = 0.11 (per month), 95% CI = 0.09 to 0.12, p < 0.001) although this increase was small and not clinically significant. …”
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Short-term association between ambient air pollution and childhood non-allergic rhinitis: A time-series study at a National Children's Regional Medical Center, in Hefei, China, fro... by Wei Cui, Hongxia Gao, Liran Zhu, Yuanyuan Xu, Haipeng Liu

“…A quasi-Poisson generalized linear regression model combined with a distributed lag nonlinear model was applied to evaluate the association between air pollution and outpatient visits for childhood NAR. …”
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The predictive role of the hs-CRP/HDL-C ratio for long-term mortality in the general population: evidence from a cohort study by Yifeng Wang, Li Wang, Zongquan Zhao, Song Yin, Xuejun Tang, Kerui Zhang

“…A two-piecewise linear regression model indicated that the risk of all-cause mortality increased more prominently when the hs-CRP/HDL-C ratio was less than 1.21. …”
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An optimized approach for predicting water quality features and a performance evaluation for mapping surface water potential zones based on Discriminant Analysis (DA), Geographical... by Abhijeet Das

“…Again, this research used a strong methodology by incorporating Machine learning (ML) algorithms, such as: Artificial Neural Network (ANN), Gaussian Process Regression (GPR), Support Vector Machine (SVM), and Linear Regression Model (LRM), were applied to forecast and confirm the quality of the water. …”
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Modeling regional aboveground carbon stock dynamics affected by land use and land cover changes by A.D. Malik, M.C.W. Arief, S. Withaningsih, P. Parikesit

“…Vegetation biomass was assessed using an allometric equation, and aboveground carbon stock data were extrapolated to the landscape scale using a linear regression model of measured carbon stocks and the Normalized Difference Vegetation Index derived from recent satellite imagery.FINDINGS: Vegetated areas were predominant in 2009 and 2021. …”
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