Confidence intervals for model parameters of an mjoint object
This function computes confidence intervals for one or more
parameters in a fitted mjoint object.
## S3 method for class 'mjoint'
confint(
object,
parm = c("Both", "Longitudinal", "Event"),
level = 0.95,
bootSE = NULL,
...
)object |
an object inheriting from class |
parm |
a character string specifying which sub-model parameter
confidence intervals should be returned for. Can be specified as
|
level |
the confidence level required. Default is |
bootSE |
an object inheriting from class |
... |
additional arguments; currently none are used. |
A matrix containing the confidence intervals for either the longitudinal, time-to-event, or both sub-models.
Graeme L. Hickey (graemeleehickey@gmail.com)
McLachlan GJ, Krishnan T. The EM Algorithm and Extensions. Second Edition. Wiley-Interscience; 2008.
Henderson R, Diggle PJ, Dobson A. Joint modelling of longitudinal measurements and event time data. Biostatistics. 2000; 1(4): 465-480.
Lin H, McCulloch CE, Mayne ST. Maximum likelihood estimation in the joint analysis of time-to-event and multiple longitudinal variables. Stat Med. 2002; 21: 2369-2382.
Wulfsohn MS, Tsiatis AA. A joint model for survival and longitudinal data measured with error. Biometrics. 1997; 53(1): 330-339.
# 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), ]
gamma <- c(0.1059417, 1.0843359)
sigma2 <- 0.03725999
beta <- c(4.9988669999, -0.0093527634, 0.0004317697)
D <- matrix(c(0.128219108, -0.006665505, -0.006665505, 0.002468688),
nrow = 2, byrow = TRUE)
set.seed(1)
fit1 <- mjoint(formLongFixed = log.lvmi ~ time + age,
formLongRandom = ~ time | num,
formSurv = Surv(fuyrs, status) ~ age,
data = hvd,
timeVar = "time",
inits = list(gamma = gamma, sigma2 = sigma2, beta = beta, D = D),
control = list(nMCscale = 2, burnin = 5)) # controls for illustration only
confint(fit1, parm = "Longitudinal")
## Not run:
# 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",
verbose = TRUE)
confint(fit2)
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.