Linear and logistic regression models are essential tools for quantifying the relationship between outcomes and exposures. Understanding the mathematics behind these models and being able to apply ...
Many observational studies aim to make causal inferences about effects of interventions or exposures on health outcomes. This course defines causation, describes how emulating a ‘target trial’ can ...
ABSTRACT: 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 ...
Capital requirements are standardized regulations for banks and other depository institutions that govern the capital, as a percentage of their assets, that they must maintain. Having this capital on ...
Abstract: Modular multilevel converters (MMCs) integrated with battery energy storage systems (BESS) enable efficient utilization of renewable energy resources such as wind and photovoltaic, while ...
ABSTRACT: This study examined the effects of using digital platforms, specifically Viazisoko and Mzizi apps, on Irish potato productivity among smallholder farmers in Molo and Njoro sub-counties, ...
Abstract: The precise forecasting of student academic performance presents a significant challenge in higher education, directly influencing curriculum development and initiatives for student ...
A Python wrapper for creating Multi-Level Models (also known as hierarchical or stratified models) using standard scikit-learn regressors. This library allows you to automatically fit independent ...
Objective Chronic kidney disease (CKD) arises due to uncontrolled hypertension (HTN). HTN significantly increases the risk of complications in vital organs, mainly the kidneys. If hypertensive ...
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