Longevity after Elections

Author

Lela Sengupta

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Adding missing grouping variables: `win_margin`, `names`, `.row`

Using data from US governors, we seek to establish a relationship between Preceptor’s longevity and the result of his campaign for the upcoming mayoral election in Newton. We have concerns that it is difficult to prove a causal relationship between election results and age, as many other covariates can confound the data. We created a gaussian linear regression model to analyze our data. Winners live about 8 years longer than losers, with a 95% confidence interval between 3 and 14.

\[death\_age_i = \beta_{0} + \beta_{1} treatment_i + \beta_{2}win\_margin_i + \\ \beta_{4}repub_i + \beta_{5}thirdparty_i + \epsilon_{i}\]

Characteristic	Beta	95% CI ¹
treatment
treatmentwin	8.4	3.1, 14
party
partyRepublican	4.0	1.1, 6.7
partyThirdparty	-9.4	-26, 6.7
win_margin	-1.4	-2.4, -0.44
¹ CI = Credible Interval