Evaluation of Active Affiliates to the SIS Multidimensional Analysis in R Shiny
Nadine ACeituno-Moya, Fred Torres-Cruz
TL;DR
This study employs multiple linear regression and an RShiny interactive tool to analyze factors influencing SIS health insurance affiliates in Peru, demonstrating significant positive effects and linear trends in enrollment data.
Contribution
It introduces an interactive RShiny application for analyzing and visualizing SIS affiliate data, combining statistical modeling with user-friendly data exploration.
Findings
Selected variables significantly influence the number of affiliates
The relationship between variables and affiliates follows a linear trend
The RShiny tool enhances data analysis and visualization capabilities
Abstract
This article presents a study that uses multiple linear regression analysis to examine the factors influencing the number of people affiliated with different insurance plans within the Comprehensive Health Insurance (SIS) system in Peru.The study highlights the importance of multiple linear regression analysis in understanding the factors that affect SIS Comprehensive Health Insurance affiliates. It also showcases the value of utilizing interactive tools like RShiny to enhance data analysis, providing a dynamic and participatory experience for researchers and users interested in the subject.To facilitate the analysis and visualization of SIS-related data, the researchers developed an interactive application using RShiny. This tool allows for the easy loading, visualization, and analysis of data in a user-friendly and practical manner. By providing an interactive platform, users can…
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Taxonomy
TopicsHealthcare Systems and Reforms