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
\[ lived\_after_i = \beta_0 + \beta_1 male_i + \beta_2 c\_election\_age_i + \\ \beta_3 male_i * c\_election\_age_i + \epsilon_i \]
Using data from all deceased gubernatorial candidates in the United States from elections held between 1945 and 2012, we seek to forecast candidate longevity in state-wide US races post-election. There is concern that longevity for gubernatorial candidates will differ significantly from that for candidates in Senate and other state-wide elections. 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.