res.model = stan_glm(y.var ~ m,
             data = dff,
             family = binomial(link = 'logit'),
             prior = student_t(df = 3, location = 0.5, scale = 1.0),
             prior_intercept = student_t(df = 7, location = 0, scale = 1.0),
             cores = 4)
y.post = posterior_predict(res.model, newdata=data.frame(m=seq(0,50,0.5)))
pp.post = apply(y.post, 2, sum)/nrow(y.post)
plot(dff$m, dff$y.var, pch=16, xlab="Measured variable score", ylab="Outcome score", cex=2, cex.lab=2, cex.axis=2)
lines(seq(0,50,0.5), pp.post)