An object returned by the
mjoint function, inheriting
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
An object of class
NULL of length 0.
A list with the following components.
a list with the estimated coefficients. The components of this list are:
the vector of fixed effects for the linear mixed effects sub-model.
the variance-covariance matrix of the random effects.
the measurement error standard deviations for the linear mixed effects sub-model.
the estimated baseline hazard values for each unique
failure time. Note that this is the centered hazard, equivalent to
that returned by
the vector of baseline covariates for the survival model and the latent association coefficient parameter estimates.
a matrix with parameter estimates at each iteration of the MCEM algorithm.
a vector with the number of Monte Carlo samples for each MCEM algorithm iteration.
a list of formulae for the fixed effects component of each longitudinal outcome.
a list of formulae for the fixed effects
component of each longitudinal outcome. The length of the list will be
a formula specifying the proportional hazards regression model (not including the latent association structure).
a list of data.frames for each longitudinal outcome.
a data.frame of the time-to-event dataset.
a character string vector of length K denoting the
column name(s) for time in
a character string denoting the column name for subject
a list giving the dimensions of model parameters with components:
a vector of the number of fixed effects for each longitudinal outcome.
a vector of the number of random effects for each longitudinal outcome.
an integer of the number of different longitudinal outcome types.
an integer of the number of baseline covariates in the time-to-event sub-model.
an integer of the total number of subjects in the study.
a vector of the number of measurements for each longitudinal outcome.
an object of class
coxph for the separate
time-to-event model fit. See
coxph for details.
a list of objects each of class
lme from fitting
separate linear mixed effects models; one per each longitudinal outcome
lme for details.
the combined log-likelihood from separate sub-model fits.
the log-likelihood from the joint model fit.
a vector of the log-likelihood values for each MCEM algorithm interaction.
a list of control parameters used in the estimation
of the joint model. See
mjoint for details.
the final number of Monte Carlo samples required prior to convergence.
the matched call.
logical: did the MCEM algorithm converge within the specified maximum number of iterations?
a vector of length 2 with each element an object of
difftime that reports the total time taken for model
fitting (including all stages) and the time spent in the EM
pfs=TRUE, indicating that post-fit statistics are to be returned,
then the output also includes the following objects.
the variance-covariance matrix of model parameters, as
approximated by the empirical information matrix, is reported. See
mjoint for details.
the square-root of the diagonal of
returned, which are estimates of the standard errors for the parameters.
a matrix with the estimated random effects values for each subject.
an array with the estimated variance-covariance matrices for the random effects values for each subject.
a list of length 3 containing the design matrices, data
frames, and vectors used in the MCEM algorithm. These are required for
prediction and to calculate the residuals and . The 3 items in the list are
l (longitudinal data),
t (time-to-event data), and
(design matrices expanded over unique failure times). These are not
intended to be extracted by the user.
Graeme L. Hickey (firstname.lastname@example.org)
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