## Not run:
# ## Random effects meta-analysis
# nstudies <- 20
# true_effects <- rnorm(nstudies, 0.5, 0.2)
# sei <- runif(nstudies, 0.05, 0.3)
# outcomes <- rnorm(nstudies, true_effects, sei)
# data1 <- data.frame(outcomes, sei)
# fit1 <- brm(outcomes | se(sei, sigma = TRUE) ~ 1,
# data = data1)
# summary(fit1)
#
# ## Probit regression using the binomial family
# n <- sample(1:10, 100, TRUE) # number of trials
# success <- rbinom(100, size = n, prob = 0.4)
# x <- rnorm(100)
# data2 <- data.frame(n, success, x)
# fit2 <- brm(success | trials(n) ~ x, data = data2,
# family = binomial("probit"))
# summary(fit2)
#
# ## Survival regression modeling the time between the first
# ## and second recurrence of an infection in kidney patients.
# fit3 <- brm(time | cens(censored) ~ age * sex + disease + (1|patient),
# data = kidney, family = lognormal())
# summary(fit3)
#
# ## Poisson model with truncated counts
# fit4 <- brm(count | trunc(ub = 104) ~ log_Base4_c * Trt_c,
# data = epilepsy, family = poisson())
# summary(fit4)
# ## End(Not run)
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