## S3 method for class 'jointModel':
ranef(object, postVar = FALSE, \dots)jointModel.TRUE the variance-covariance matrix of these estimates is also returned.
See Details for more info.postVar = TRUE, the numeric matrix has an extra attribute ``postVar".
}
author{Dimitris Rizopoulos email{d.rizopoulos@erasmusmc.nl}}
seealso{code{coef.jointModel}, code{fixef.jointModel}}
examples{
# linear mixed model fit
fitLME <- lme(log(serBilir) ~ drug * year, random = ~ 1 | id, data = pbc2)
# survival regression fit
fitSURV <- survreg(Surv(years, status2) ~ drug, data = pbc2.id, x = TRUE)
# joint model fit, under the (default) Weibull model
fitJOINT <- jointModel(fitLME, fitSURV, timeVar = "year")
ranef(fitJOINT)
}
keyword{methods}"ch-GH", "weibull-GH", "ph-GH" the ranef() method returns the
posterior means (and posterior variances if postVar = TRUE), whereas for method "ch-Laplace" it returns the
posterior modes (and the inverse of the negative of the second-order derivative of the log-posterior with respect to the
random effects, if postVar = TRUE).