ES MI PRIMERA CHAMBA

Primera actividad de Rmarkdown con los chicos de lTI 2026-1

Primer_Documento_RMarkdown_Diseño

MAPPA STARLINK CON 5G

Workshop 2 Solution - Econometric Models Alberto Dorantes, Ph.D. Tec de Monterrey

This document presents an applied statistical modeling lab using data from the 2023 Behavioral Risk Factor Surveillance System (BRFSS), a nationally representative U.S. health survey. The analysis demonstrates key regression modeling concepts in epidemiology including simple and multiple logistic regression, dummy variable coding, interaction testing, model diagnostics, and model comparison, all applied to predicting hypertension among U.S. adults. Key topics covered include building and interpreting logistic regression models, controlling for confounding, testing for effect modification using likelihood ratio tests, checking model assumptions with variance inflation factors and Cook's Distance, and selecting the best fitting model using AIC and BIC. Results show that age and obesity are the strongest independent predictors of hypertension in this sample, with no significant Age × BMI interaction detected. This lab was completed as part of EPID 553 Statistical Inference and is intended as a practical introduction to regression modeling for public health and epidemiology students.