How to be an idiot with priors in R

an-idiot-approach-to-priors.R

library(tidyverse)
library(stevedata)
library(brms)

# what follows is me being an idiot. Don't be Steve. Don't be an idiot.

?therms

# For anyone with a brain: the better you think of Obama, the worse you think of Trump (and vice-versa).

M1 <- lm(fttrump1 ~ ftobama1, data=therms)
summary(M1)

# But I'm choosing to be an idiot, so let's use that and be an idiot with prior distributions in R.
# Let's flip the sign of that coefficient/standard error, and then proceed to more idiocy.

idiot_prior1 <- c(set_prior("normal(.653, .015)", class="b", coef="ftobama1"))
idiot_prior2 <- c(set_prior("normal(6.53, .015)", class="b", coef="ftobama1"))
idiot_prior3 <- c(set_prior("normal(65.3, .015)", class="b", coef="ftobama1"))

B1 <- brm(fttrump1 ~ ftobama1,
          data=therms,
          seed = 8675309,
          prior = idiot_prior1,
          family = gaussian())
          
B2 <- brm(fttrump1 ~ ftobama1,
          data=therms,
          seed = 8675309,
          prior = idiot_prior2,
          family = gaussian())
          
B3 <- brm(fttrump1 ~ ftobama1,
          data=therms,
          seed = 8675309,
          prior = idiot_prior3,
          family = gaussian())
          
summary(B1)
summary(B2)
summary(B3)

# ^ don't be an idiot with prior distributions in your Bayesian analyses.