Extracts the random effects estimates from a fitted joint model.
# S3 method for JMbayes
ranef(object, postVar = FALSE, …)
an object inheriting from class JMbayes
.
logical; if TRUE
the variance of the posterior distribution is also returned.
additional arguments; currently none is used.
a numeric matrix with rows denoting the individuals and columns the random effects (e.g., intercepts, slopes, etc.).
If postVar = TRUE
, the numeric matrix has an extra attribute ``postVar".
Rizopoulos, D. (2012) Joint Models for Longitudinal and Time-to-Event Data: with Applications in R. Boca Raton: Chapman and Hall/CRC.
# NOT RUN {
# linear mixed model fit
fitLME <- lme(log(serBilir) ~ drug * year, random = ~ 1 | id, data = pbc2)
# survival regression fit
fitSURV <- coxph(Surv(years, status2) ~ drug, data = pbc2.id, x = TRUE)
# joint model fit, under the (default) Weibull model
fitJOINT <- jointModelBayes(fitLME, fitSURV, timeVar = "year")
ranef(fitJOINT)
# }
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