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Once a model has been fitted using runMetaAnalysis, replacement functions are defined for each function argument. This allows to quickly tweak one or more analysis settings, which are implemented once the rerun function is called.

Usage

data(x) <- value
which.run(x) <- value
es.measure(x) <- value
es.type(x) <- value
es.var(x) <- value
se.var(x) <- value
es.binary.raw.vars(x) <- value
method.tau(x) <- value
i2.ci.threelevel(x) <- value
nsim.boot(x) <- value
hakn(x) <- value
study.var(x) <- value
arm.var.1(x) <- value
arm.var.2(x) <- value
measure.var(x) <- value
low.rob.filter(x) <- value
method.tau.ci(x) <- value
which.combine(x) <- value
which.combine.var(x) <- value
which.outliers(x) <- value
which.influence(x) <- value
which.rob(x) <- value
nnt.cer(x) <- value
rho.within.study(x) <- value
phi.within.study(x) <- value
w1.var(x) <- value
w2.var(x) <- value
vcov(x) <- value
near.pd(x) <- value
use.rve(x) <- value
html(x) <- value
lower.is.better(x) <- value
selmodel.steps(x) <- value
rerun(m)

Arguments

x

Object of class runMetaAnalysis.

value

Value of one of the arguments in runMetaAnalysis or correctPublicationBias

m

(Adapted) object of class runMetaAnalysis.

Examples

if (FALSE) {
data("depressionPsyCtr")
depressionPsyCtr %>%
  checkDataFormat() %>%
  checkConflicts() %>%
  calculateEffectSizes() %>% 
  filterPoolingData(condition_arm2 %in% 
                      c("wl", "other ctr")) -> data

m <- runMetaAnalysis(data, "combined")

# Compare results when other tau^2 estimator is used
method.tau(m) <- "DL"
rerun(m)
}