This function takes the results of a
jointmeta1 fit and bootstraps
it to find the standard errors of the parameter estimates.
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the number of bootstraps to conduct. Note that confidence
intervals will only be calculated if
the number of quadrature points over which the integration with
respect to the random effects will be performed. Will default to
the maximum number of iterations that the EM algorithm will perform for each bootstrap fit. Will default to 350.
the tolerance level before convergence of the algorithm is considered to have occurred. Default value is tol = 0.001.
this argument determines the level of printing that is
done during the bootstrapping. If
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
n.boot bootstraps to determine the standard errors of the
parameter estimates, and their confidence intervals if
n.boot > 100.
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 is a binary treatment indicator
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
sub-model 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
a list containing three elements:
a data frame containing the estimates, standard errors and 95 and any overall effects requested.
the covariance matrix for the model parameters
a data frame containing the results of each bootstrap
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## 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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