# Fit a classical univariate joint model with a single longitudinal outcome
# and a single time-to-event outcome
data(heart.valve)
hvd <- heart.valve[!is.na(heart.valve$log.grad) & !is.na(heart.valve$log.lvmi), ]
set.seed(1)
fit1 <- mjoint(formLongFixed = log.lvmi ~ time + age,
formLongRandom = ~ time | num,
formSurv = Surv(fuyrs, status) ~ age,
data = hvd,
timeVar = "time",
control = list(nMCscale = 2, burnin = 5)) # controls for illustration only
plot(fit1, param = "beta") # LMM fixed effect parameters
plot(fit1, param = "gamma") # event model parameters
if (FALSE) {
# Fit a joint model with bivariate longitudinal outcomes
data(heart.valve)
hvd <- heart.valve[!is.na(heart.valve$log.grad) & !is.na(heart.valve$log.lvmi), ]
fit2 <- mjoint(
formLongFixed = list("grad" = log.grad ~ time + sex + hs,
"lvmi" = log.lvmi ~ time + sex),
formLongRandom = list("grad" = ~ 1 | num,
"lvmi" = ~ time | num),
formSurv = Surv(fuyrs, status) ~ age,
data = list(hvd, hvd),
inits = list("gamma" = c(0.11, 1.51, 0.80)),
timeVar = "time",
control = list(burnin = 50),
verbose = TRUE)
plot(fit2, type = "convergence", params = "gamma")
}
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