# NOT RUN {
fit1 <- brm(time | cens(censored) ~ age * sex + disease + (1|patient),
data = kidney, family = gaussian("log"))
summary(fit1)
## remove effects of 'disease'
fit2 <- update(fit1, formula. = ~ . - disease)
summary(fit2)
## remove the group specific term of 'patient' and
## change the data (just take a subset in this example)
fit3 <- update(fit1, formula. = ~ . - (1|patient),
newdata = kidney[1:38, ])
summary(fit3)
## use another family and add population-level priors
fit4 <- update(fit1, family = weibull(), inits = "0",
prior = set_prior("normal(0,5)"))
summary(fit4)
# }
# NOT RUN {
# }
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