REmrt function

Random effects meta-tree

A function to fit a random effects meta-tree

REmrt(
  formula,
  data,
  vi,
  c = 1,
  maxL = 5,
  minsplit = 6,
  cp = 1e-05,
  minbucket = 3,
  xval = 10,
  lookahead = FALSE,
  ...
)

Arguments

• formula: A formula, with a response variable (usually the effect size) and the potential moderator variables but no interaction terms.
• data: A data frame of a meta-analytic data set, including the study effect sizes, sampling variance, and the potential moderators.
• vi: sampling variance of the effect size.
• c: A non-negative scalar.The pruning parameter to prune the initial tree by the "c*standard-error" rule.
• maxL: the maximum number of splits
• minsplit: the minimum number of studies in a parent node before splitting
• cp: the stopping rule for the decrease of between-subgroups Q. Any split that does not decrease the between-subgroups Q is not attempted.
• minbucket: the minimum number of the studies in a terminal node
• xval: the number of folds to perform the cross-validation
• lookahead: an argument indicating whether to apply the "look-ahead" strategy when fitting the tree
• ...: Additional arguments to be passed.

Returns

If (a) moderator effect(s) is(are) detected, the function will return alist including the following objects:

tree: A data frame that represents the tree, with the Q-between and the residual heterogeneity (tau^2) after each split.

n: The number of the studies in each subgroup

moderators: the names of identified moderators

Qb: The between-subgroups Q-statistic

tau2: The estimate of the residual heterogeneity

df: The degrees of freedom of the between-subgroups Q test

pval.Qb: The p-value of the between-subgroups Q test

g: The subgroup summary effect size, based on Hedges'g

se: The standard error of subgroup summary effect size

zval: The test statistic of the subgroup summary effect size

pval: The p-value of the test statistic of the subgroup summary effect size

ci.lb: The lower bound of the confidence interval

ci.ub: The upper bound of the confidence interval

call: The matched call

cv.res: The cross-validation table

data: the data set subgrouped by the fitted tree

If no moderator effect is detected, the function will return a listincluding the following objects:

n: The total number of the studies

Q: The Q-statistics for the heterogeneity test

df: The degree of freedoms of the heterogeneity test

pval.Q: The p-value for the heterogeneity test

g: The summary effect size for all studies (i.e., the overall effect size)

se: The standard error of the summary effect size

zval: The test statistic of the summary effect size

pval: The p-value for the test statistic of the summary effect size

ci.lb: The lower bound of the confidence interval for the summary effect size

ci.ub: The upper bound of the confidence interval for the summary effect size

call: The matched call

Examples

data(dat.BCT2009)
library(Rcpp)
REtree <- REmrt(g ~ T1 + T2+ T4 +T25, vi = vi, data = dat.BCT2009, c = 0)
summary(REtree)
plot(REtree)

See Also

summary.REmrt, plot.REmrt