Analysis

We have data about US voters in 1992, and we are trying to analyze it. We are not sure if representativeness holds. We are using a model from the brms package, using the categorical family, with the dependent variable being who was voted for. We modeled pres_vote, a character variable, as a multinomial logistic regression model. Women are most likely to support Clinton.

✖ 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)	0.45	0.31, 0.60
muPerot_(Intercept)	-0.85	-1.1, -0.64
muClinton_sexMale	-0.25	-0.48, -0.03
muPerot_sexMale	0.42	0.14, 0.69
1 CI = Credible Interval

Adding missing grouping variables: `.row`