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Surveys are often used to study health behavior and determine the risks of disease. Meanwhile, seemingly every day, news outlets publish a different "research says" article about how to lose weight (fast! with no effort at all!). In this project, you will use survey data of ~20k people sampled from the United States to explore health behaviors associated with lower Body Mass Index (BMI), a standardized measure of healthy weight and obesity. Surveys with complex designs use special statistical methods to incorporate sampling weights and design factors into the estimation and inference. Incorporating survey design methods, you will use multiple regression to handle confounders when testing whether physical activity is associated with lower BMI.
You will apply the skills you learned in Analyzing Survey Data in R and Multiple and Logistic Regression, as well as apply many skills from Introduction to the Tidyverse, including summarizing data and visualizing with ggplot2.
This project will use National Health and Nutrition Examination Survey (NHANES) data from ~20,000 participants surveyed in years 2009-2012 found in the NHANES R package.
Assistant Professor of Biostatistics at Oregon Health & Science University
Jessica is an Assistant Professor of Biostatistics in the OHSU-PSU School of Public Health at Oregon Health & Science University. Her statistical research interests include risk prediction with high dimensional data sets and the analysis of genetic and other omics data. She is passionate about teaching R and programming, reproducible research, and open science.See More