Description
An object returned by the mjoint function, inheriting
from class mjoint and representing a fitted joint model for
multivariate longitudinal and time-to-event data. Objects of this class
have methods for the generic functions coef, logLik,
plot, print, ranef, fixef, summary,
AIC, getVarCov, vcov, confint, sigma,
and formula.Value
A list with the following components. coefficients- a list with the estimated coefficients. The
components of this list are:
beta- the vector of fixed effects for the linear mixed effects
sub-model.
D- the variance-covariance matrix of the random effects.
sigma2- the measurement error standard deviations for the
linear mixed effects sub-model.
haz- the estimated baseline hazard values for each unique
failure time.
gamma- the vector of baseline covariates for the survival
model and the latent association coefficient parameter estimates.
history- a matrix with parameter estimates at each iteration
of the MCEM algorithm.
nMC.hx- a vector with the number of Monte Carlo samples for
each MCEM algorithm iteration.
formLongFixed- a list of formulae for the fixed effects
component of each longitudinal outcome.
formLongRandom- a list of formulae for the fixed effects
component of each longitudinal outcome. The length of the list will be
equal to
formLongFixed. formSurv- a formula specifying the proportional hazards
regression model (not including the latent association structure).
data- a list of data.frames for each longitudinal outcome.
survData- a data.frame of the time-to-event dataset.
timeVar- a character string vector of length K denoting the
column name(s) for time in
data. id- a character string denoting the column name for subject
IDs in
data and survData. dims- a list giving the dimensions of model parameters with
components:
p- a vector of the number of fixed effects for each
longitudinal outcome.
r- a vector of the number of random effects for each
longitudinal outcome.
K- an integer of the number of different longitudinal outcome
types.
q- an integer of the number of baseline covariates in the
time-to-event sub-model.
n- an integer of the total number of subjects in the study.
nk- a vector of the number of measurements for each
longitudinal outcome.
sfit- an object of class
coxph for the separate
time-to-event model fit. See coxph for details. lfit- a list of objects each of class
lme from fitting
separate linear mixed effects models; one per each longitudinal outcome
type. See lme for details. log.lik0- the combined log-likelihood from separate sub-model
fits.
log.lik- the log-likelihood from the joint model fit.
ll.hx- a vector of the log-likelihood values for each MCEM
algorithm interaction.
control- a list of control parameters used in the estimation
of the joint model. See
mjoint for details. finalnMC- the final number of Monte Carlo samples required
prior to convergence.
call- the matched call.
conv- logical: did the MCEM algorithm converge within the
specified maximum number of iterations?
comp.time- an object of class
difftime that reports the
time taken for model fitting.
Format
An object of class NULL of length 0.Post model fit statistics
If pfs = TRUE, indicating that post-fit statistics are to be
returned, then the output also includes the following objects. vcov- the variance-covariance matrix of model parameters, as
approximated by the empirical information matrix, is reported. See
mjoint for details. SE.approx- the square-root of the diagonal of
vcov is
returned, which are estimates of the standard errors for the parameters. Eb- a matrix with the estimated random effects values for each
subject.
Vb- an array with the estimated variance-covariance matrices
for the random effects values for each subject.
dmats- a list of length 3 containing the design matrices, data
frames, and vectors used in the MCEM algorithm. These are required to
calculated the residuals. The 3 items in the list are
l
(longitudinal data), t (time-to-event data), and z (design
matrices expanded over unique failure times). These are not intended to be
extracted by the user.