Atwebembere/GYTS_Publication-Multivariate_logistic_regression

Exposure to tobacco content and the risk of initiation of tobacco use among nonsmoking adolescents (13-15 years)? A secondary analysis of the 2018 Global Youth Tobacco Survey conducted in Uganda. # 2018 Global Youth Tobacco Survey, Uganda **Project Title** Exposure to tobacco content and the risk of initiation of tobacco use among nonsmoking adolescents (13-15 years)? A secondary analysis of the 2018 Global Youth Tobacco Survey conducted in Uganda. **Description** This project examines the association between gender and the future risk of tobacco use among nonsmoking adolescents aged 13–15 years in Uganda. Using data from the 2018 Global Youth Tobacco Survey (GYTS), the analysis evaluates predictors of tobacco use, including peer influence, parental smoking, and exposure to anti-smoking advertisements. The goal is to inform strategies for preventing tobacco use in low- and middle-income countries. **Features** Full analysis provided in a reproducible R Markdown file (analysis.Rmd). Includes data wrangling, visualization, and statistical modeling steps. Use of Logistic regressions to analyze predictors. **Contents** analysis.Rmd: The R Markdown file containing all code, analyses, and visualizations. README.md: A guide to understanding and reproducing this project. LICENSE: Licensing information. **Requirements** To reproduce the analysis, ensure you have the following: **Software:** R (version 4.4.1 or higher) RStudio R Packages (loaded via pacman): haven: Imports and exports data in various formats, such as SPSS, SAS, and Stata. readr: Provides efficient functions for reading and writing rectangular data (CSV, TSV, etc.) into R, offering faster and more user-friendly methods than base R. tidyverse: A collection of packages that make data science tasks easier and more consistent. It includes packages for data manipulation (dplyr), visualization (ggplot2), tidying data (tidyr), and more. table1: Generates publication-ready tables, typically used for summarizing descriptive statistics or presenting baseline characteristics in clinical studies. DiagrammeR: Allows you to create diagrams and flowcharts, such as flow diagrams, network graphs, and more c …