logistic regression

Logistic Regression in R

Introduction In this post, I’ll introduce the logistic regression model in a semi-formal, fancy way. Then, I’ll generate data from some simple models: 1 quantitative predictor 1 categorical predictor 2 quantitative predictors 1 quantitative predictor with a quadratic term I’ll model data from each example using linear and logistic regression. Throughout the post, I’ll explain equations, terms, output, and plots. Here are some key takeaways:

Presidential primary candidate name recognition matters

Key takeaway FiveThirtyEight claims that early national primary polls can become more useful for predicting party nomination success if one takes candidate name recognition into account. But so few low-name recognition candidates have won their party’s nomination that you cannot reasonably predict whether a low-name recognition candidate will win their party’s nomination over a high-name recognition candidate, no matter their national polling averages. You can better predict nomination success using early national polling averages only, and you can make an even more informed prediction if you take political party into account.

2020 Democratic Presidential Primary Polling Averages

R Shiny Application and GitHub repository for 2020 Democratic Presidential Primary Polling Averages