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How to be an idiot with priors in 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.
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