# simple logistic regression simulation
require(MCMCpack)
require(ggplot2)

a = 1
b = 2
n = 1000
x = rnorm(n)
z = a + b*x
pr = 1/(1+exp(-z))
y = rbinom(n,1,pr)
df = data.frame(y=y,x=x)
model <- glm(y ~ x,family="binomial",data=df)
bayes <- MCMClogit(y~x,data=df)

ggplot(df,aes(x=x,y=y))+geom_point()+stat_smooth(method="glm",se=FALSE)