N Parameters

Author

Sophia Yao

Using a dataset of the primary elections in 2006 in Michigan from Gerber, Green, and Larimer (2008), we seek to find the causal effect of postcards on voting in the 2026 Texas election. If certain groups of people are less likely to respond to postcards, for example they might not check their mail regularly, the sample of voters who actually received and potentially read the postcards might not be representative of the overall voting population. In this model, age is positively related to voter turnout, indicating that as age increases, so does the likelihood of voting.

\[ y_{i} = \beta_{0} + \beta_{1} age\_z + \beta_{2}male_i + \beta_{3}civic\_duty_i + \\ \beta_{4}hawthorne_i + \beta_{5}self_i + \beta_{6}neighbors_i + \\ \beta_{7}Sometimes\ vote_i + \beta_{8}Always\ vote_i + \\ \beta_{9}civic\_duty_i Sometimes\ vote_i + \beta_{10}hawthorne_i Sometimes\ vote_i + \\ \beta_{11}self_i Sometimes\ vote_i + \beta_{11}neighbors_i Sometimes\ vote_i + \\ \beta_{12}civic\_duty_i Always\ vote_i + \beta_{13}hawthorne_i Always\ vote_i + \\ \beta_{14}self_i Always\ vote_i + \beta_{15}neighbors_i Always\ vote_i + \epsilon_{i} \]

Warning in tidy.brmsfit(x, ..., effects = "fixed"): some parameter names
contain underscores: term naming may be unreliable!

Characteristic

Beta

95% CI

1
(Intercept) 0.155 0.137, 0.174
age_z 0.036 0.031, 0.042
sex

    sexMale 0.004 -0.005, 0.014
treatment

    No Postcard
    treatmentCivicDuty 0.016 -0.027, 0.057
    Hawthorne 0.004 -0.037, 0.043
    Self -0.007 -0.049, 0.035
    Neighbors 0.084 0.041, 0.126
voter_class

    Rarely Vote
    voter_classSometimesVote 0.115 0.095, 0.135
    voter_classAlwaysVote 0.298 0.275, 0.321
treatment * voter_class

    treatmentCivicDuty * voter_classSometimesVote -0.005 -0.051, 0.043
    Hawthorne * voter_classSometimesVote 0.010 -0.033, 0.054
    Self * voter_classSometimesVote 0.059 0.012, 0.106
    Neighbors * voter_classSometimesVote -0.009 -0.057, 0.038
    treatmentCivicDuty * voter_classAlwaysVote -0.009 -0.061, 0.045
    Hawthorne * voter_classAlwaysVote 0.034 -0.017, 0.086
    Self * voter_classAlwaysVote 0.047 -0.007, 0.100
    Neighbors * voter_classAlwaysVote -0.002 -0.056, 0.050
1

CI = Credible Interval