Description Usage Arguments Value
Function to calculate joint likelihood used in the jointmeta1 function
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data 
an object of class jointdata containing the variables named in the model formulae 
longdat 
the longitudinal data with factors and interaction terms expanded, ordered by increasing survival time 
survdat 
the survival data with factors and interaction terms expanded, ordered by increasing survival time 
q 
the number of individual level random effects 
likeests 
a list of values required to calculated the loglikelihood for the fitted joint model. This list has the following elements:

lgpt 
the number of quadrature points which the loglikelihood is
evaluated over following a model fit. This defaults to 
studies 
the names of the studies present in the supplied data 
p1 
the number of fixed effects included in the longitudinal submodel 
p2 
the number of fixed effects included in the survival submodel 
long.rand.ind 
a vector of character strings to indicate what variables
to assign individual level random effects to. A maximum of three
individual level random effects can be assigned. To assign a random
intercept include 'int' in the vector. To not include an individual level
random intercept include 'noint' in the vector. For example to fit a model
with individual level random intercept and random slope set

randstart.ind 
a list of the conditional modes of the individual level random effects in each study given the data and the estimates of the separate longitudinal model parameters 
randstart.ind.cov 
a list of the conditional covariance matrices for each individual for the individual level random effects given the data and the estimates of the separate longitudinal model parameters 
r 
the number of study level random effects (if included in the model) 
long.rand.stud 
a vector of character strings to indicate what
variables to assign study level random effects to. If no study level
random effects then this either not specified in function call or set to

randstart.stud 
a data frame containing the conditional modes of the
study level random effects given the data and the estimates of the separate
longitudinal model parameters. This is only present if study level random
effects were specified in the 
randstart.stud.cov 
a list of conditional covariance matrices for each
study for the study level random effects given the data and the estimates
of the separate longitudinal model parameters. This is only present if
study level random effects were specified in the 
strat 
logical value: if 
study.name 
a character string denoting the name of the variable in the
baseline dataset in 
id.name 
character string specifying the id variable in the dataset 
A list containing three elements:
log.like
the overall loglikelihood for the fitted joint model.
longlog.like
the portion of the loglikelihood attributable to the longitudinal submodel.
survlog.like
the portion of the loglikelihood attributable to the survival submodel.
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