n-parameters
We are trying to determine the causal effect of receiving a postcard how people vote in the upcoming Texas election, with how it can change with their past engagement. A specific problem that casts doubt on our approach is the unmeasured factors that can change the change of receiving a postcard or voting. A linear regression model is being used with the dependent variable being voting in the election. Age, gender, and past voting behavior are the independent variables. There is a relationship with how past voting behavior is linked to voting in the upcoming election.
\[y_{i} = \beta_{0} + \beta_{1} age\_z + \beta_{2}male_i + \beta_{3}civic\_duty_i + \\ \beta_{4}hawthorne_i + \beta_{5}self_i + \beta_{6}neighbors_i + \\ \beta_{7}Sometimes\ vote_i + \beta_{8}Always\ vote_i + \\ \beta_{9}civic\_duty_i Sometimes\ vote_i + \beta_{10}hawthorne_i Sometimes\ vote_i + \\ \beta_{11}self_i Sometimes\ vote_i + \beta_{11}neighbors_i Sometimes\ vote_i + \\ \beta_{12}civic\_duty_i Always\ vote_i + \beta_{13}hawthorne_i Always\ vote_i + \\ \beta_{14}self_i Always\ vote_i + \beta_{15}neighbors_i Always\ vote_i + \epsilon_{i}\]
Warning in tidy.brmsfit(x, ..., effects = "fixed"): some parameter names
contain underscores: term naming may be unreliable!Characteristic |
Beta |
95% CI 1 |
|---|---|---|
| (Intercept) | 0.156 | 0.138, 0.175 |
| age_z | 0.036 | 0.031, 0.041 |
| sex | ||
| sexMale | 0.004 | -0.005, 0.013 |
| treatment | ||
| No Postcard | — | — |
| treatmentCivicDuty | 0.015 | -0.028, 0.058 |
| Hawthorne | 0.004 | -0.038, 0.044 |
| Self | -0.008 | -0.050, 0.034 |
| Neighbors | 0.083 | 0.039, 0.127 |
| voter_class | ||
| Rarely Vote | — | — |
| voter_classSometimesVote | 0.114 | 0.094, 0.134 |
| voter_classAlwaysVote | 0.297 | 0.275, 0.320 |
| treatment * voter_class | ||
| treatmentCivicDuty * voter_classSometimesVote | -0.004 | -0.051, 0.044 |
| Hawthorne * voter_classSometimesVote | 0.011 | -0.034, 0.057 |
| Self * voter_classSometimesVote | 0.059 | 0.012, 0.106 |
| Neighbors * voter_classSometimesVote | -0.008 | -0.056, 0.039 |
| treatmentCivicDuty * voter_classAlwaysVote | -0.008 | -0.062, 0.044 |
| Hawthorne * voter_classAlwaysVote | 0.035 | -0.017, 0.088 |
| Self * voter_classAlwaysVote | 0.048 | -0.006, 0.101 |
| Neighbors * voter_classAlwaysVote | -0.001 | -0.055, 0.052 |
| 1
CI = Credible Interval |
||