gmvjoint (version 0.4.0)

ranef.joint: Extract random effects from a joint object.

Description

Return the random effects \(\hat{\boldsymbol{b}}\) which maximises the complete data log-likelihood at the MLEs \(\hat{\Omega}\).

Usage

# S3 method for joint
ranef(object, Var = FALSE, ...)

Value

A matrix containing required random effects effects. If Var=TRUE, instead a list is returned with first element the matrix of random effects and second a matrix of the variances \(\hat{\Sigma}\). Note that these are posterior modes

of the random effects. Conditional distribution can be found by cond.ranefs.

Arguments

object

a joint model fit by the joint function.

Var

logical, should the estimated variance of the random effects at \(\hat{\Omega}\) be returned? Defaults to Var=FALSE.

...

additional arguments (none used).

Author

James Murray ().

See Also

fixef.joint cond.ranefs

Examples

# \donttest{
# Univariate fit on PBC data -----------------------------------------
data(PBC)

# Subset data and remove NAs
PBC <- subset(PBC, select = c('id', 'survtime', 'status', 'drug', 'time',
                              'albumin'))
PBC <- na.omit(PBC) 

# Specify univariate fit
long.formulas <- list(
  albumin ~ time*drug + (1 + time|id)
)
surv.formula <- Surv(survtime, status) ~ drug

fit <- joint(long.formulas, surv.formula, PBC, family = list('gaussian'))
b <- ranef(fit, FALSE)
# }