Adding missing grouping variables: `.row`
Four Parameters: Categorical
To answer the question “what was the relationship between sex and voting in the 1992 US Presidential election among supporters of the three leading candidates: Clinton, Bush and Perot?” we are using the American National Election Studies (ANES) survey data from 1992. If the survey is not representative of the voting population then the results will not be applicable. Men seem to prefer Perot.
\[\begin{aligned} \rho_{clinton} &=& \frac{e^{\beta_{0, clinton} + \beta_{1, clinton} male}}{1 + e^{\beta_{0, clinton} + \beta_{1, clinton} male}}\\ \rho_{perot} &=& \frac{e^{\beta_{0, perot} + \beta_{1, perot} male}}{1 + e^{\beta_{0, perot} + \beta_{1, perot} male}}\\ \rho_{bush} &=& 1 - \rho_{clinton} - \rho_{perot} \end{aligned}\]Warning in tidy.brmsfit(x, ..., effects = "fixed"): some parameter names
contain underscores: term naming may be unreliable!✖ Unable to identify the list of variables.
This is usually due to an error calling `stats::model.frame(x)`or `stats::model.matrix(x)`.
It could be the case if that type of model does not implement these methods.
Rarely, this error may occur if the model object was created within
a functional programming framework (e.g. using `lappy()`, `purrr::map()`, etc.).Characteristic |
Beta |
95% CI 1 |
|---|---|---|
| muClinton_(Intercept) | 0.46 | 0.31, 0.60 |
| muPerot_(Intercept) | -0.85 | -1.1, -0.64 |
| muClinton_sexMale | -0.26 | -0.48, -0.04 |
| muPerot_sexMale | 0.42 | 0.14, 0.70 |
| 1
CI = Credible Interval |
||