Description Usage Arguments Details Value Examples
This function takes the results of a jointmeta1
fit and bootstraps
it to find the standard errors of the parameter estimates.
1 2 3 4 5 6 7 8 9  jointmetaSE(
fitted,
n.boot,
gpt,
max.it,
tol,
print.detail = FALSE,
overalleffects = NULL
)

fitted 
a 
n.boot 
the number of bootstraps to conduct. Note that confidence
intervals will only be calculated if 
gpt 
the number of quadrature points over which the integration with
respect to the random effects will be performed. Will default to

max.it 
the maximum number of iterations that the EM algorithm will perform for each bootstrap fit. Will default to 350. 
tol 
the tolerance level before convergence of the algorithm is considered to have occurred. Default value is tol = 0.001. 
print.detail 
this argument determines the level of printing that is
done during the bootstrapping. If 
overalleffects 
this argument indicates what if any overall effects
will have their standard errors and confidence intervals calculated
during the bootstrap procedure. An example of an overall effect would be
the combined value of a treatment effect, and a treatment by study
membership interaction. The overall treatment effect (the sum of these
two values) could be of interest in an investigation. This argument is a
list containing two elements, 
This function takes the results of a one stage joint model fit to
data from multiple studies using the function jointmeta1
and
performs n.boot
bootstraps to determine the standard errors of the
parameter estimates, and their confidence intervals if
n.boot > 100
.
The parameter overalleffects
is designed for use in cases where
interaction terms are included in the model specification, for example
a model fitted using jointmeta1
which includes both treat
and treat:study
where treat
is a binary treatment indicator
variable and study
is a study indicator. In this case it may be of
interest to calculate the confidence interval for the value of
treat + treat:study
for a given study. This is done by calculating
the value of the expression for each bootstrap, and calculating the
standard errors for the expression in the same way as for the other
parameters. Any overall effects to be calculated for the longitudinal
submodel are supplied as a list named long
in the list
overalleffects
, with each element of this list containing a vector
of the character names of the fixed effects to be summed to form an
overall effect. Overall effects from the survival model are specified in
a similar way to an element named surv
a list containing three elements:
results
a data frame containing the estimates, standard errors and 95 and any overall effects requested.
covmat
the covariance matrix for the model parameters
bootstraps
a data frame containing the results of each bootstrap
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18  ## Not run:
jointdat<tojointdata(longitudinal = simdat2$longitudinal,
survival = simdat2$survival, id = "id",
longoutcome = "Y",
timevarying = c("time","ltime"),
survtime = "survtime", cens = "cens",
time = "time")
onestagefit4 < jointmeta1(data = jointdat,
long.formula = Y ~ 1 + time + treat + study,
long.rand.ind = c("int", "time"),
long.rand.stud = c("treat"),
sharingstrct = "randprop",
surv.formula = Surv(survtime, cens) ~ treat,
study.name = "study", strat = TRUE)
onestagefit4SE < jointmetaSE(fitted = onestagefit4, n.boot = 200)
## End(Not run)

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