Hello,

Regarding the example here with standard package and stan_glm() function for Bayesian logistic regression

https://www.kaggle.com/avehtari/bayesian-logistic-regression-with-rstanarm

```
library(rstanarm)
options(mc.cores = parallel::detectCores())
t_prior <- student_t(df = 7, location = 0, scale = 2.5)
post1 <- stan_glm(outcome ~ ., data = diabetes,
family = binomial(link = "logit"),
prior = t_prior, prior_intercept = t_prior, QR=TRUE,
seed = 14124869)
```

The OR is

```
OR = post1$measure[2,1]
```

**I would like to ask some questions please:**

- How I can use non-informative prior (flat)? with different cutoff points?
- How I can perform queries since its Bayesian, like P(OR>0.2)?
- How I can get the plot of prior, likelihood, and the posterior as well?

Thanks in advance.