Warning: package 'brms' was built under R version 4.4.1Warning: package 'Rcpp' was built under R version 4.4.1Warning: package 'tidybayes' was built under R version 4.4.1Warning: package 'gtsummary' was built under R version 4.4.1Five Parameters
Using data from all deceased candidates for governor in the United States between 1945 and 2011, we seek to forecast candidate longevity post-election for candidates running in campaigns between 2000 and 2050. There is concern that the average lifespan may have changed significantly over the years. We are using a Bayesian regression model with the formula lived_after ~ sex * election_age to analyze the data, where lived_after is the dependent variable representing post-election life expectancy. The model reveals that the interaction between sex and election age has a positive direction, suggesting that as election age increases, the life expectancy difference between male and female governors tends to widen. Male candidates live (on average) 15 years longer than female candidates after election, with a confidence interval of 10 to 20 years more.
\[ lived\_after_i = \beta_0 + \beta_1 male_i + \beta_2 c\_election\_age_i + \\ \beta_3 male_i * c\_election\_age_i + \epsilon_i \]