Background The role of mineralocorticoid receptor antagonists (MRAs) in acute myocardial infarction (MI) remains ...
Introduction While a large proportion of buccal mucosa cancer (BMC) is attributed to tobacco use, the contribution of alcohol is little-known. In India, alcohols include internationally-recognised ...
Introduction The global evidence base on intimate partner violence (IPV) prevalence and risk factors is predominantly cross-sectional, limiting clarity in changes over time. Prospective cohort data ...
Background Few studies have investigated patient-reported non-motor outcomes after stroke in young adults. We aimed to assess ...
Multiple sclerosis is an autoimmune disease in which immune cells attack and destroy the protective myelin sheaths that surround nerve fibres, leading to neurological disturbances. After spinal cord ...
Will Kenton is an expert on the economy and investing laws and regulations. He previously held senior editorial roles at Investopedia and Kapitall Wire and holds a MA in Economics from The New School ...
This study examined the relationship between the Monetary Policy Rate (MPR) and inflation across five continents from 2014 to 2023 using both Frequentist and Bayesian Linear Mixed Models (LMM). It ...
The New Type Key Think Tank of Zhejiang Province “China Research Institute of Regulation and Public Policy”, Hangzhou, China. 2 Shandong Province City Water Supply and Drainage Water Quality ...
Abstract: A time-space (TS) traffic diagram, which presents traffic states in time-space cells with color, is an important traffic analysis and visualization tool. Despite its importance for ...
Advertising Sales Prediction using Multiple Linear Regression is a data analysis project that aims to predict sales based on advertising spending using multiple linear regression. The project involves ...
Description: Omitted variables are one of the most important threats to the identification of causal effects. In linear models, the well known Omitted Variable Bias formula shows how an omitted ...
Abstract: Time series forecasting plays a key role in many fields such as business, energy or environment. Traditionally, statistical or machine learning models for time series forecasting are trained ...
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